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The mitochondrial unfolded protein response inhibits pluripotency acquisition and mesenchymal-to-epithelial transition in somatic cell reprogramming

Nature Metabolism volume 7, pages 940–951 (2025)Cite this article

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Abstract

The mitochondrial unfolded protein response (UPRmt), a mitochondria-to-nucleus retrograde pathway that promotes the maintenance of mitochondrial function in response to stress, plays an important role in promoting lifespan extension in Caenorhabditis elegans1,2. However, its role in mammals, including its contributions to development or cell fate decisions, remains largely unexplored. Here, we show that transient UPRmt activation occurs during somatic reprogramming in mouse embryonic fibroblasts. We observe a c-Myc-dependent, transient decrease in mitochondrial proteolysis, accompanied by UPRmt activation at the early phase of pluripotency acquisition. UPRmt impedes the mesenchymal-to-epithelial transition (MET) through c-Jun, thereby inhibiting pluripotency acquisition. Mechanistically, c-Jun enhances the expression of acetyl-CoA metabolic enzymes and reduces acetyl-CoA levels, thereby affecting levels of H3K9Ac, linking mitochondrial signalling to the epigenetic state of the cell and cell fate decisions. c-Jun also decreases the occupancy of H3K9Ac at MET genes, further inhibiting MET. Our findings reveal the crucial role of mitochondrial UPR-modulated MET in pluripotent stem cell plasticity. Additionally, we demonstrate that the UPRmt promotes cancer cell migration and invasion by enhancing epithelial-to-mesenchymal transition (EMT). Given the crucial role of EMT in tumour metastasis3,4, our findings on the connection between the UPRmt and EMT have important pathological implications and reveal potential targets for tumour treatment.

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Fig. 1: c-Myc-induced UPRmt activation inhibits pluripotency acquisition.
Fig. 2: The activated UPRmt inhibits MET through c-Jun in pluripotency acquisition.
Fig. 3: The activated UPRmt decreases histone acetylation and occupancy at MET genes.
Fig. 4: c-Jun regulates the levels of acetyl-CoA and inhibits histone acetylation during UPRmt activation.

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Data availability

The data and materials that support the findings of this study are available from the corresponding author (X.L.) upon reasonable request. The RNA-seq and CUT&Tag raw data have been deposited in the Genome Sequence Archive at the Beijing Institute of Genomics Data Center at the Chinese Academy of Sciences (RNA-seq accession number: CRA014321; CUT&Tag accession number: CRA018794). The RNA-seq data for the hepatic differentiation of human ES cells are available in the GEO (accession number: GSE70741). All other relevant data supporting the key findings of this study are available within the article and its Supplementary Information files. Source data are provided with this paper.

Code availability

There was no custom code used.

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Acknowledgements

We are grateful to all members of X. Liu’s laboratory for useful discussions. We thank the J. Liu lab at the Guangzhou Institutes of Biomedicine and Health for the c-Jun overexpression plasmids. We also thank the entire staff of the Public Instrument Center at Guangzhou Institutes of Biomedicine and Health, CAS. Our work was financially supported by the National Key Research and Development Program of China (2023YFE0210100), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0480000), the National Natural Science Foundation projects of China (32025010, 32488301, 92254301, 92357302, 92157202, 32241002, 32261160376, 32100619, 32170747, 32322022, 32370782, 32371007, 32300608, 32300620, 32471358, 32461160288), the National Key Research and Development Program of China (2024YFA0916400, 2022YFE0210100, 2024YFA1802302, 2022YFA1103800), the NSFC/RGC Joint Grant Scheme 2022/2023 (N_CUHK 428/22), Major Project of Guangzhou National Laboratory (GZNL2024A03006, GZNL2024B01003) the Key Research Program, CAS (ZDBS-ZRKJZ-TLC003), the CAS Project for Young Scientists in Basic Research (YSBR-075), the Guangdong Province Science and Technology Program (2023B0303000023, 2023B1111050005, 2023A1515030231, 2022A1515110493, 2023B1212060050, 2021B1515020096, 2022A1515110951, 2023B1212120009, 2024A1515010782, 2024B1515040020, 2024A1515030120, 2023TQ07A024, 2024A1515012839), the Guangzhou Science and Technology Program (202206060002, 2023A04J0414, 2025A04J2106, 2025A04J7110, 2025A04J5485, 2023A04J0863, 2023A04J0727), Health@InnoHK funding support from the Innovation Technology Commission of the Hong Kong SAR, CAS Youth Innovation Promotion Association (to Y. Wu and K.C.) and the Basic Research Project of Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences.

Author information

Author notes

  1. These authors contributed equally: Zhongfu Ying, Yanmin Xin, Zihuang Liu.

Authors and Affiliations

  1. GMU-GIBH Joint School of Life Sciences, State Key Lab of Respiratory Disease, The Guangdong-Hong Kong-Macao Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou Municipal and Guangdong Provincial Key Laboratory of Protein Modification and Degradation, Guangzhou Medical University; Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China

    Zhongfu Ying, Yanmin Xin, Tianxin Tan, Xuejun Hong, Qiuzhi Li, Gaoshen Liu, Qi Meng, Shihe Zhou, Yao Yao, Ge Xiang, Linpeng Li, Yi Wu, Miaohui Mu, Wenxi Liang & Xingguo Liu

  2. Centre for Regenerative Medicine and Health, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong SAR, China

    Zhongfu Ying, Zihuang Liu, Yile Huang, Yingzhe Ding, Zifeng Ruan, Yaofeng Wang, Duanqing Pei & Xingguo Liu

  3. Center for Development and Regeneration, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, Guangdong-Hong Kong Joint Laboratory for Stem Cell and Regenerative Medicine, GIBH-CUHK Joint Research Laboratory on Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, China-New Zealand Joint Laboratory on Biomedicine and Health, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China

    Zhongfu Ying, Yanmin Xin, Zihuang Liu, Tianxin Tan, Xuejun Hong, Qiuzhi Li, Gaoshen Liu, Qi Meng, Shihe Zhou, Wenxin Li, Yao Yao, Ge Xiang, Linpeng Li, Yi Wu, Yang Liu, Miaohui Mu, Zifeng Ruan, Wenxi Liang, Junwei Wang & Xingguo Liu

  4. University of Chinese Academy of Sciences, Beijing, China

    Zihuang Liu, Wenxin Li & Yang Liu

  5. State Key Laboratory of Wheat Improvement, College of Life Sciences, Shandong Agricultural University, Tai’an, China

    Chong Li

  6. Guangdong Engineering Research Center of Early Clinical Trials of Biotechnology Drugs, The Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou, China

    Jingyi Guo, Baojian Liao & Dajiang Qin

  7. School of Biomedical Sciences, The University of Hong Kong, Hong Kong SAR, China

    Yang Liu

  8. CUHK-GIBH Joint Research Laboratory on Stem Cells and Regenerative Medicine, CUHK-Jinan University Key Laboratory for Regenerative Medicine, Ministry of Education, School of Biomedical Sciences, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China

    Wuming Wang, Gang Lu & Wai-Yee Chan

  9. Laboratory of Cell Fate Control, School of Life Sciences, Westlake University, Hangzhou, China

    Duanqing Pei

Authors
  1. Zhongfu Ying
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  2. Yanmin Xin
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  3. Zihuang Liu
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Contributions

X.L. conceived, designed and supervised the project. Z.Y. and Y.X. designed and carried out most experiments. Z.Y. and Y.X. carried out most data analyses. Z.L. carried out experiments involving cancer cells and Hsp60 and performed data analysis. Y.H. and Y.D. carried out RNA-seq, CUT&Tag and metabolome analyses. T.T., X.H., Q.L., G. Liu, Z.R. and W.L. performed western blot experiments. J.G., S.Z., Y.Y., Q.M., L.L., Y. Wu, Y.L. (Chinese Academy of Sciences), M.M. and W.L. participated in cell culture. J.W. helped with flow cytometery. Z.R., G.X., B.L., C.L. and Y.L. (The University of Hong Kong) participated in data analysis. Y. Wang, D.Q., W.W., G. Lu, D.P. and W.-Y.C. gave suggestions. X.L. and Z.Y. wrote the manuscript.

Corresponding authors

Correspondence to Zhongfu Ying or Xingguo Liu.

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Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Metabolism thanks Danica Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editor: Yanina-Yasmin Pesch, in collaboration with the Nature Metabolism team.

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Extended data

Extended Data Fig. 1 Transient increased UPRmt inhibits pluripotency acquisition.

a, The relative band densities of Fig. 1a; n = 4; **P = 0.0078 (D3 vs D0), *P = 0.019 (D5 vs D3). b, The expression of Hsp60 at days 0, 2, 4, 6, and 8 during mESCs to EBs differentiation. c, The expression of Hsp60 at days 0, 3, 5, and 8 during somatic cell reprogramming with TOMM20 as an internal reference. d, The expression of Hsp60 in EpiSCs, mESCs and 2CLCs. e, The relative band densities of Fig. 1d; n = 4; **P = 0.0042. f, The expression of Hsp60 after Flag, Sox2, Klf4 or Oct4 transduced at days 0 and 3. g, The relative band densities of Fig. 1e; n = 4; ***P = 0.00043 (Flag vs SKOM), ***P = 0.0006 (SKO vs SKOM). h, The expression of Hsp60 at days 0, 3, 5, and 8 during SKO mediated somatic cell reprogramming. i, The relative band densities of Fig. 1f; n = 4 (Control vs CDDOme) or n = 3 (Control vs knockdown of Lonp1 or Pitrm1); **P = 0.0039, *P = 0.019 (Control siRNA vs Lonp1 siRNA), *P = 0.013 (Control siRNA vs Pitrm1 siRNA). j, The expression of Hsp60 and Hsp70 after knockdown of Hsp60 at day 3 of reprogramming. k, The relative numbers of GFP+ colonies after knockdown of Hsp60; n = 5; ***P = 7.74 × 10−5. Data are presented as mean ± SEM; * P < 0.05; ** P < 0.01; *** P < 0.001. Unpaired two-tailed student’s t test (a, e, g, i, and k). n represents the number of biological replicates.

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Extended Data Fig. 2 GO terms of differentially expressed genes in control and UPRmt activated cells.

a, GO terms of downregulated genes in CDDOme treated cells. b, GO terms of upregulated and downregulated genes in Lonp1 or Pitrm1 knockdown cells. Statistical significance was determined by two-way analysis of variance, and wilcoxon testing was used to correct for multiple testing.

Extended Data Fig. 3 UPRmt inhibits MET during reprogramming.

a, The relative band densities of Fig. 2b; n = 3 (Control vs CDDOme) or n = 4 (Control vs knockdown of Lonp1 or Pitrm1); *P = 0.045 (E-cadherin, Control vs CDDOme), *P = 0.027 (E-cadherin, Control siRNA vs Lonp1 siRNA), **P = 0.0022 (E-cadherin, Control siRNA vs Pitrm1 siRNA); *P = 0.045 (Slug, Control vs CDDOme), *P = 0.038 (Slug, Control siRNA vs Lonp1 siRNA), **P = 0.0045 (Slug, Control siRNA vs Pitrm1 siRNA). b, Real time PCR analysis of the MET relative genes after CDDOme treatment or Lonp1 or Pitrm1 knockdown at day 3 of reprogramming; n = 4 (Control vs CDDOme) or n = 3 (Control vs knockdown of Lonp1 or Pitrm1); For Control vs CDDOme, ***P (E-cadherin)= 2.44 × 10−5, **P (Epcam)= 0.005, **P (Slug)= 0.0022, *P (Snail)= 0.03, **P (Zeb1)= 0.0025; For Control siRNA vs Lonp1 siRNA, **P (E-cadherin)= 0.0033, ***P (Epcam)= 0.0006, *P (Slug)= 0.028, *P (Snail)= 0.025, *P (Zeb1)= 0.015; For Control siRNA vs Pitrm1 siRNA, *P (E-cadherin)= 0.048, *P (Epcam)= 0.021, **P (Slug)= 0.0053, *P (Snail)= 0.034, *P (Zeb1)= 0.016. c, Western blot analysis of Hsp60, Hsp70, E-cadherin and Slug after Hsp60 knockdown at days 3 of somatic cell reprogramming. d, e, Representative images (d) and quantification (e) of scratch assays on day 3 after CDDOme treatment or Lonp1 or Pitrm1 knockdown during reprogramming; Scale bar: 100 μm; n = 3; **P = 0.0091 (Control vs CDDOme), *P = 0.03 (Control siRNA vs Lonp1 siRNA), *P = 0.017 (Control siRNA vs Pitrm1 siRNA). f, g, Representative images (f) and quantification (g) of scratch assays at day 3 after Hsp60 knockdown during reprogramming; Scale bar: 200 μm; n = 3; *P = 0.043. Data are presented as mean ± SEM; * P < 0.05; ** P < 0.01; *** P < 0.001. Unpaired two-tailed student’s t test (a, b, e, and g). n represents the number of biological replicates.

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Extended Data Fig. 4 UPRmt regulates MET and EMT during epithelial cell reprogramming or cells differentiation.

a, The expression of Hsp60 at days 0, 3, 5, and 8 during mammary epithelial cell (MEC) reprogramming. b, Western blot analysis of E-cadherin and Slug after CDDOme treatment or knockdown of Lonp1 or Pitrm1 at day 3 of MEC reprogramming. c, AP staining analysis of the efficiency of the MEC reprogramming after CDDOme treatment or knockdown of Lonp1 or Pitrm1. d, Plots of UPRmt responsive gene expression and epithelial genes at days 0, 1, 2, 3, 5, 7, 9 and 11 during human embryonic stem cells differentiation to hepatocytes. The black lines represent the average expression levels of these genes (6 genes) by day. e, Western blot analysis of E-CADHERIN and SLUG after CDDOme treatment or Lonp1 or Pitrm1 knockdown at day 3 and day 7 during human embryonic stem cells differentiation to hepatocytes. f, Western blot analysis of E-cadherin and Slug at days 0, 5, 7 and 10 during the differentiation of mouse embryonic stem cells into cardiac cells. g, Western blot analysis of E-cadherin and Slug after CDDOme treatment or Lonp1 or Pitrm1 knockdown at day 7 and 10 during the differentiation of mouse embryonic stem cells into cardiac cells.

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Extended Data Fig. 5 UPRmt enhances EMT in cancer cells.

a, Western blot analysis of HSP60, E-CADHERIN and SLUG after CDDOme treatment in indicated concentration for 24 hours in the lung cancer cell line H1299. b, Representative images and quantification of scratch assays after CDDOme treatment in H1299; Scale bar: 100 μm; n = 3; **P = 0.0097. c, Representative images and quantification of invasion assays after CDDOme treatment in H1299; Scale bar: 100 μm; n = 3; *P = 0.017. d, Western blot analysis of HSP60, E-CADHERIN and SLUG after CDDOme treatment in indicated concentration for 24 hours in the liver cancer cell line HepG2. e, Representative images and quantification of invasion assays after CDDOme treatment in HepG2; Scale bar: 100 μm; n = 3, *P = 0.027. Data are mean ± SEM; * P < 0.05; ** P < 0.01. Unpaired two-tailed student’s t test (b, c, and e). n represents the number of biological replicates.

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Extended Data Fig. 6 c-Jun is involved in UPRmt activation in reprogramming.

a, The expression of Hsp60 at day 3 with Atf4, Atf5 or Chop knockdown. b, The expression of Hsp60 at day 3 with Atf4, Atf5 or Chop overexpression. c, The expression of Hsp60 at day 3 with miR-200c, miR-21a or miR-367 inhibitor. d, The relative band densities of Fig. 2c; n = 3; *P = 0.025. e, The relative band densities of Fig. 2d; n = 3; *P = 0.017 (Control siRNA vs c-Jun siRNA 1), ***P = 0.00018, *P = 0.048 (Control siRNA vs c-Jun siRNA 3). f, The relative band densities of Fig. 2e; n = 3; *P = 0.048 (Control vs CDDOme), *P = 0.026 (Control siRNA vs Lonp1 siRNA), *P = 0.016 (Control siRNA vs Pitrm1 siRNA). g, The expression of c-Jun, Sirt7 and Atf5 at days 0, 3, 5, and 8 during SKOM mediated somatic cell reprogramming. h, The relative band densities of Fig. 2f; n = 4; For E-cadherin, left, *P = 0.02 (Control siRNA vs c-Jun siRNA), *P = 0.034 (Control siRNA vs Control siRNA plus CDDOme), **P = 0.0077 (Control siRNA plus CDDOme vs c-Jun siRNA plus CDDOme); middle, *P = 0.034 (Control siRNA vs c-Jun siRNA), **P = 0.0096 (Control siRNA vs Lonp1 siRNA), *P = 0.011 (Lonp1 siRNA vs c-Jun siRNA plus Lonp1 siRNA); right, *P = 0.031 (Control siRNA vs c-Jun siRNA), *P = 0.031 (Control siRNA vs Pitrm1 siRNA), *P = 0.047 (Pitrm1 siRNA vs c-Jun siRNA plus Pitrm1 siRNA); For Slug, left, *P = 0.016 (Control siRNA vs c-Jun siRNA), *P = 0.022 (Control siRNA vs Control siRNA plus CDDOme), **P = 0.0082 (Control siRNA plus CDDOme vs c-Jun siRNA plus CDDOme); middle, *P = 0.037 (Control siRNA vs c-Jun siRNA), *P = 0.045 (Control siRNA vs Lonp1 siRNA), *P = 0.031 (Lonp1 siRNA vs c-Jun siRNA plus Lonp1 siRNA); right, **P = 0.0053 (Control siRNA vs c-Jun siRNA), *P = 0.036 (Control siRNA vs Pitrm1 siRNA), *P = 0.026 (Pitrm1 siRNA vs c-Jun siRNA plus Pitrm1 siRNA). Data are mean ± SEM; * P < 0.05; ** P < 0.01; *** P < 0.001. Unpaired two-tailed student’s t test (d-f, and h). n represents the number of biological replicates.

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Extended Data Fig. 7 Metabolomics analysis after UPRmt activation during reprogramming.

a, Metabolomics analysis with CDDOme treatment at day 3 of reprogramming. Orange dots indicate upregulated metabolites, whereas the green dot indicates the lone downregulated metabolite, acetyl-CoA. Unpaired two-tailed student’s t test. b, Heatmap showing the levels of metabolites in control and CDDOme treated cells. Red indicates upregulated metabolites, whereas blue indicates downregulated metabolite.

Extended Data Fig. 8 Activated UPRmt decreases histone acetylation and occupancy at MET genes.

a, Western blot analysis of H3Ac, H3K4Ac, H3K14Ac, H3K18Ac and H3K27Ac with or without UPRmt activation at day 3 of reprogramming. b, The relative band densities of Fig. 3b; n = 4 (Control vs CDDOme); n = 3 (Control vs knockdown of Lonp1 or Pitrm1); *P = 0.014 (Control vs CDDOme), *P = 0.017 (Control siRNA vs Lonp1 siRNA), *P = 0.029 (Control siRNA vs Pitrm1 siRNA). c, The relative band densities of Fig. 3c; CDDOme treatment: *P = 0.028 (Acetate), **P = 0.0091 (Citrate), *P = 0.043 (Pyruvate); Lonp1 siRNA: *P = 0.04 (Acetate), *P = 0.021 (Citrate), *P = 0.022 (Pyruvate); Pitrm1 siRNA: *P = 0.048 (Acetate), *P = 0.047 (Citrate), *P = 0.0497 (Pyruvate); n = 3. d, CUT&Tag analysis of H3K9Ac binding to epithelial genes with or without UPRmt activation at day 3 of reprogramming. e, The relative band densities of Fig. 3e; CDDOme treatment: *P = 0.016 (Acetate), *P = 0.047 (Citrate), *P = 0.022 (Pyruvate); Lonp1 siRNA: *P = 0.02 (Acetate), **P = 0.0018 (Citrate), *P = 0.016 (Pyruvate); Pitrm1 siRNA: *P = 0.01 (Acetate), *P = 0.03 (Citrate), ***P = 4.76 × 10−5 (Pyruvate); n = 3. Data are mean ± SEM; * P < 0.05; ** P < 0.01; *** P < 0.001. Unpaired two-tailed student’s t test (b, c, and e). n represents the number of biological replicates.

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Extended Data Fig. 9 Expression analysis of histone acetylation, acetyl-CoA and acetyl-CoA associated enzymes with or without c-Jun knockdown after UPRmt activation.

a, The relative band densities of Fig. 4a; left, *P = 0.037 (Control siRNA vs Control siRNA plus CDDOme), *P = 0.029 (Control siRNA plus CDDOme vs c-Jun siRNA plus CDDOme); middle, *P = 0.013 (Control siRNA vs Lonp1 siRNA), *P = 0.029 (Lonp1 siRNA vs c-Jun siRNA plus Lonp1 siRNA); right, **P = 0.0015 (Control siRNA vs Pitrm1 siRNA), *P = 0.047 (Pitrm1 siRNA vs c-Jun siRNA plus Pitrm1 siRNA); n = 3. b, Western blot analysis of H3K27Ac after UPRmt activation with or without c-Jun knockdown at day 3 of reprogramming. c, d, Relative acetyl-CoA levels analysis after c-Jun overexpression (c) or knockdown (d) at day 3 of reprogramming; *P = 0.017 (c); *P = 0.019 (d); n = 3. e, qPCR analysis of acetyl-CoA metabolic enzymes (Acat1, Acat2 and Acot12) in CDDOme-treated or Lonp1 or Pitrm1 knockdown cells with or without c-Jun knockdown at day 3 of reprogramming; For (CDDOme plus Control siRNA) vs (CDDOme plus c-Jun siRNA), *P = 0.028 (Acat1), *P = 0.015 (Acat2), *P = 0.016 (Acot12); For (Lonp1 siRNA plus Control siRNA) vs (Lonp1 siRNA plus c-Jun siRNA), *P = 0.016 (Acat1), *P = 0.015 (Acat2), **P = 0.0048 (Acot12); For (Pitrm1 siRNA plus Control siRNA) vs (Pitrm1 siRNA plus c-Jun siRNA), **P = 0.0072 (Acat1), *P = 0.045 (Acat2), *P = 0.011 (Acot12); n = 3. f, qPCR analysis of acetyl-CoA generating enzymes (Acss2, Acly and Pdha1) and metabolic enzyme (Acaca) after UPRmt activation with or without c-Jun knockdown at day 3 of reprogramming; n = 4. Data are mean ± SEM; * P < 0.05; ** P < 0.01. Unpaired two-tailed student’s t test (a and c-f). n represents the number of biological replicates.

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Extended Data Fig. 10 c-Jun regulates acetyl-CoA levels by binding to the gene loci of acetyl-CoA metabolic enzymes during UPRmt activation.

a, The relative band densities of Fig. 4c; *P = 0.018 (Control siRNA vs c-Jun siRNA); *P = 0.013 (Control siRNA vs Control siRNA plus CDDOme), *P = 0.024 (Control siRNA plus CDDOme vs c-Jun siRNA plus CDDOme); *P = 0.049 (Control siRNA vs Lonp1 siRNA), *P = 0.035 (Lonp1 siRNA vs c-Jun siRNA plus Lonp1 siRNA); **P = 0.0022 (Control siRNA vs Pitrm1 siRNA), **P = 0.0015 (Pitrm1 siRNA vs c-Jun siRNA plus Pitrm1 siRNA); n = 3. b, Relative acetyl-CoA levels in Acat1, Acat2 or Acot12 knockdown cells with c-Jun overexpression at day 3 of reprogramming; *P = 0.04 (Acat1 siRNA), *P = 0.012 (Acat2 siRNA), *P = 0.015 (Acot12 siRNA); n = 3. c, ChIP-qPCR analysis of c-Jun binding to Acat1, Acat2 and Acot12 with or without UPRmt activation at day 3 of reprogramming; For CDDOme vs Control, *P = 0.033 (Acat1), **P = 0.0063 (Acat2), **P = 0.0018 (Acot12); For Lonp1 siRNA vs control siRNA, *P = 0.047 (Acat1), *P = 0.014 (Acat2), *P = 0.01 (Acot12); For Pitrm1 siRNA vs control siRNA, *P = 0.022 (Acat1), *P = 0.037 (Acat2), *P = 0.011 (Acot12); n = 4. Data are mean ± SEM; * P < 0.05; ** P < 0.01. Unpaired two-tailed student’s t test (a-c). n represents the number of biological replicates.

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Ying, Z., Xin, Y., Liu, Z. et al. The mitochondrial unfolded protein response inhibits pluripotency acquisition and mesenchymal-to-epithelial transition in somatic cell reprogramming. Nat Metab 7, 940–951 (2025). https://doi.org/10.1038/s42255-025-01261-6

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