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Mitochondrial fission factor senses and governs ferroptosis

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Data availability

All data supporting this study are available in the article, its Supplementary Information and deposited databases. The phosphoproteomic data have been deposited into ProteomeXchange via iProX (accession PXD079759). The metabolomic data have been deposited to Mendeley Data (https://doi.org/10.17632/93m6cpvhcp.1). Public databases referenced in this study (KEGG, HMDB, LIPID Maps and Gene Ontology) are described in the Methods. Gene OE screen data for Fig. 1d are provided in Supplementary Table 1. Uncropped western blot scans are provided in Supplementary Fig. 1. FACS gating strategies are provided in Supplementary Fig. 2. Source data are provided with this paper.

Code availability

No custom code was used in this study. All data analyses were performed using publicly or commercially available software as detailed in the Methods.

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Acknowledgements

We gratefully acknowledge L. Scorrano for expert advice and insightful comments on the mitochondrial studies in this work; S. Yang from the laboratory of F. Wang for providing the ischaemia–reperfusion model; members of the Zhang, Min, Wang and Fu laboratories for their critical reading and insightful suggestions; staff at Novogene for performing the phosphoproteomic MS, untargeted metabolomic and eicosanoid metabolomic analyses; J. Wang from the Core Facilities, Zhejiang University School of Medicine for providing technical support; and staff at the Laboratory Animal Center at Zhejiang University for their help with xenograft experiments.

Funding

This work was supported by the National Natural Science Foundation of China (no. 82073412 to Q.Z; no. 32330047 to F.W.; no. 82471593 and 82188102 to J.M.; no. 82473894 to C.F.; no. 82574628 to Q.B) and the Dean’s Funding of the School of Basic Medical Sciences, Basic Medical Innovation Research Institute, Zhejiang University to Q.Z.; the Shanghai Oriental Talents Program (no. BJWS2024061) and the National Key R&D Program of China (no. 2022YFF0606703) to Q.B.; the Postdoctoral Fellowship Program of CPSF (no. GZC20251521 to Xinquan Yang), and the Starry Night Science Fund at the Shanghai Institute for Advanced Study, Zhejiang University (SN-ZJU-SIAS-0020 to F.W. and J.M.).

Author information

Author notes

  1. These authors contributed equally: Songjun Dai, Xiaoyan Dai, Tingting Zhang, Yuanyuan Qi, Xinquan Yang

Authors and Affiliations

  1. The First Affiliated Hospital, Zhejiang Key Laboratory of Frontier Medical Research on Cancer Metabolism, The Second Affiliated Hospital, Department of Orthopedic Surgery, State Key Laboratory of Experimental Hematology, Institute of Translational Medicine, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China

    Songjun Dai, Tingting Zhang, Yuanyuan Qi, Xinquan Yang, Pengfei Diao, Chaodong Ge, Wenxiang Huang, Jisheng Ran, Xueliang Yang, Peng Zhang, Ruijun Wang, Junxia Min, Fudi Wang & Qiang Zhang

  2. Zhejiang Provincial Engineering Research Center of New Technologies and Applications for Targeted Therapy of Major Diseases, Zhejiang Provincial Key Laboratory of Drug Discovery and Development for Metabolic Diseases, College of Life Sciences and Medicine, Zhejiang Sci-Tech University, Hangzhou, China

    Xiaoyan Dai, Keke Zheng, Hong Qian & Caiyun Fu

  3. Global Innovation Institute of Element Science (GIIES-JLU), The First Hospital of Jilin University, Changchun, China

    Xinquan Yang, Chaodong Ge & Fudi Wang

  4. Zhejiang Key Laboratory of Motor System Disease Precision Research and Therapy, Hangzhou, China

    Jisheng Ran

  5. Jiangsu Key Laboratory of Marine Pharmaceutical Compound Screening, College of Pharmacy, Jiangsu Ocean University, Lianyungang, China

    Kunxiao Zhang

  6. Boguan Biotechnologies, Yantai, China

    Junbing Wu

  7. Science and Technology Innovation Center, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China

    Qian Ba

Authors

  1. Songjun Dai
  2. Xiaoyan Dai
  3. Tingting Zhang
  4. Yuanyuan Qi
  5. Xinquan Yang
  6. Pengfei Diao
  7. Chaodong Ge
  8. Wenxiang Huang
  9. Jisheng Ran
  10. Xueliang Yang
  11. Peng Zhang
  12. Keke Zheng
  13. Ruijun Wang
  14. Hong Qian
  15. Kunxiao Zhang
  16. Junbing Wu
  17. Caiyun Fu
  18. Qian Ba
  19. Junxia Min
  20. Fudi Wang
  21. Qiang Zhang

Contributions

Conceptualization: Q.Z., S.D., F.W., J.M., Q.B. and C.F. Bioinformatics: Q.B. Cell biology and biochemical assays: S.D., Y.Q., W.H. and Xueliang Yang. Immunoblotting: X.D., S.D. and J.R. Tumour xenograft experiments: T.Z., S.D., X.D., K. Zheng and H.Q. In vivo toxicity experiments: Xinquan Yang., C.G. and P.Z. Phosphatase library construction: P.D., R.W. and K. Zhang. Writing: S.D., J.M., X.D. and J.W. Supervision: Q.Z., F.W. and J.M.

Corresponding authors

Correspondence to Caiyun Fu, Qian Ba, Junxia Min, Fudi Wang or Qiang Zhang.

Ethics declarations

Competing interests

J.W. is an employee of Boguan Biotechnologies. The other authors declare no competing interests.

Peer review

Peer review information

Nature thanks Carsten Culmsee and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Global phosphoproteomic changes under distinct cell death stimuli.

a, Viability of HeLa cells treated with RSL3, STS, TCZ, and TRCZ for 12 h, or erastin for 24 h. The final drug concentrations used for mass spectrometry are indicated by red arrows. Related to Fig. 1a. b, Hierarchical clustering analysis of common phosphosites across all samples. c,d, Weighted gene co-expression network analysis (WGCNA) of phosphosites in response to distinct cell death stimuli. (c) Hierarchical clustering of module phosphosites that summarize the modules found in the clustering analysis and treatments (module + trait). The heatmap shows the adjacencies in the module phosphosites network, including the trait weight. (d) Modules and traits (cell death) relationship analysis. Correlations between module phosphosites and traits are shown in the table, with p values shown in parentheses. e–g, Hierarchical clustering analysis of phosphosites in the blue module (associated with ferroptosis) (e), the black module (associated with apoptosis) (f) and the green module (associated with necroptosis) (g). The top GOBP and KEGG terms enriched from phosphoproteins are listed on the right. h, Target-gene mRNA levels in HeLa cells expressing shNC or shRNAs targeting the genes analyzed in Fig. 1e. n = 3 independent repeats (a,h). Data are mean ± s.d., analyzed by one-way ANOVA. NS, not significant.

Source data

Extended Data Fig. 2 MFF deletion confers resistance to ferroptosis.

a, Immunoblotting of MFF in CRISPR Ctrl, MFF KO and MFF-reconstructed HeLa cells. b, Viability of cells in a after RSL3 for 24 h or erastin for 48 h. c, GSH/GSSG ratios in wild-type or MFF KO HeLa cells treated with 200 nM RSL3 or 2 µM FINO2 for 6 h, with or without 2 µM Lip-1 pretreatment for 0.5 h. d, Cell death in CRISPR Ctrl, MFF KO and MFF-rescued HeLa cells treated with vehicle, 50 µM hemin for 48 h, or hemin after 100 µM DFO pretreatment for 0.5 h. e, Cell death in CRISPR Ctrl or MFF KO cells treated for 24 h with organic peroxides (20 µM TBHP, 10 µM CHP or 50 µM BPO) or 250 µM H2O2, with or without Lip-1 as indicated. f,g, Cell density (f) and EdU incorporation (g) in wild-type or MFF KO HeLa cells. Scale bars, 50 µm. h, Immunoblotting and cell viability in HeLa, HT-1080, SH-SY5Y, HepG2 and A549 cells expressing shNC or MFF-targeting shRNAs after RSL3 treatment for 24 h. i,j, Viability of HeLa cells expressing shNC or MFF-targeting shRNAs after STS or TNFα + CHX (i), or TNFα + CHX+zVAD (j), for 24 h. k, LDH release in cells as in i after indicated RSL3 concentrations for 24 h. l,n, Lipid peroxidation (l) and intracellular ROS (n) in HeLa cells expressing shNC or MFF-targeting shRNAs after 200 nM RSL3 for 6 h, with or without Lip-1 as indicated. m, Cell morphology of HeLa cells expressing shNC or MFF-targeting shRNAs after 200 nM RSL3 for 6 h, with or without 10 µM Fer-1 pretreatment for 0.5 h; dead cells are green. Scale bars, 50 µm. o, Immunoblotting, cell viability and lipid peroxidation in wild-type or DRP1 KO HeLa cells. For viability, cells were treated with the indicated concentrations of RSL3 for 24 h; for lipid peroxidation, cells were treated with 200 nM RSL3 for 6 h. p, SIM images of mitochondrial morphology in wild-type, MFF KO and DRP1 KO HeLa cells. Scale bars, 5 µm. q, Co-immunoprecipitation of MFF and DRP1 in HeLa cells co-expressing 3×Flag-MFF and DRP1-GFP after 200 nM RSL3 for indicated times. r, Immunoblotting of MFF and DRP1 in control, MFF/DRP1 DKO and those cells reconstituted with MFF and/or DRP1. s, Lipid peroxidation in cells as in r after 200 nM RSL3 for 6 h, with or without Lip-1 as indicated. t, Model of DRP1 recruitment by distinct adaptors during mitochondrial and peroxisomal fission. u–w, Immunoblotting, viability and lipid peroxidation in HeLa cells expressing shNC or shRNAs targeting FIS1 (u), MIEF1 (v) or MIEF2 (w), treated as in o. x, Immunoblotting of MFF, MFN1 and MFN2 in control, MFF KO, MFF/MFN1 DKO and MFF/MFN2 DKO HeLa cells. y, Cell death and lipid peroxidation in cells as in x, with or without Lip-1 as indicated. For cell death, cells were treated with 150 nM RSL3 for 24 h; for lipid peroxidation, cells were treated with 200 nM RSL3 for 6 h. n = 3 (c-f,j-l,n,y) and 4 (b,h-i) biological replicates; for panels o,s,u-w, n = 3 (lipid peroxidation) and 4 (viability) biological replicates; n = 16 representative fields (g). Data are mean ± s.d. (b-f,h-l,n,o,s,u-w,y) or mean ± s.e.m. (g), analyzed by two-sided Student’s t-tests (g) or two-way ANOVA (b-e,h-l,n,o,s,u-w,y). NS, not significant. Schematic in t created in BioRender; Zhang, P. https://biorender.com/rg1lgxi (2026).

Source data

Extended Data Fig. 3 Ferroptotic stress triggers MFF-dependent mitochondrial fission and dysfunction.

a, Time-lapse imaging of mitochondrial morphology in U-2 OS cells stained with MitoTracker Red and Hoechst, treated with 1 µM RSL3 or 25 µM erastin at 0 h, with or without 0.5-h pretreatment with 2 µM Lip-1 or 50 µM BME. b,c, Immunoblotting of SLC7A11 (b) or GPX4 (c) and confocal images of mitochondrial morphology in SLC7A11 KO HeLa cells with or without BME withdrawal (b), or GPX4 KO cells with or without Trolox withdrawal (c). d, Time-lapse imaging and single cell relative fluorescence intensity (RFI) quantification of lipid peroxidation, mitochondrial membrane potential, mitochondrial ROS and cell death in HeLa cells stained with C11-BODIPY581/591, TMRE/SYTOX Green or MitoSOX Red/SYTOX Green after 200 nM RSL3 addition at 0 h. e–h, Mitochondrial morphology in HeLa cells expressing sgNC or DRP1-targeting sgRNAs (e), or shNC or shRNAs targeting FIS1 (f), MIEF1 (g) or MIEF2 (h), after 200 nM RSL3 for 4 h. i,j, Mitochondrial ROS in CRISPR Ctrl or MFF KO (i), and CRISPR Ctrl or DRP1 KO (j) HeLa cells treated for 12 h with 20 µM TBHP, 10 µM CHP, 50 µM BPO or 250 µM H2O2, with or without 2 µM Lip-1 pretreatment for 0.5 h. k, Flow-cytometry quantification of C11-BODIPY, MitoSOX Red, TMRE or SYTOX Green signals in wild-type or MFF KO HeLa cells after 200 nM RSL3 addition at 0 min; red arrows indicate the first time points showing significant differences. l, Flow-cytometric fluorescence ratios and cell viability in HeLa cells expressing mito-HyPer7-DAAO after D- or L-alanine preincubation for 4 h, with or without 10 µM Fer-1 pretreatment for 0.5 h, and 200 nM RSL3 for 4 h. Scale bars, 5 µm (a–h). n = 3 biological replicates (i-l) and 3 representative fields (d). Data are mean ± s.d. (i–l) or mean ± s.e.m. (d), analyzed by one-way ANOVA (l) or two-way ANOVA (i-l). NS, not significant.

Source data

Extended Data Fig. 4 MFF-dependent peroxisomal remodeling governs ferroptosis via PPARα-mediated β-oxidation.

a, Confocal images of peroxisomal morphology in HeLa cells stably expressing GFP-PTS1 treated with vehicle, 200 nM RSL3 for 4 h, or RSL3 after 0.5-h pretreatment with 2 µM Lip-1; alternatively, cells were treated with vehicle, 25 µM erastin for 12 h, or erastin after 0.5-h pretreatment with 50 µM BME. Dashed boxes outline individual cells. Quantification of peroxisome number is shown at right. b, Co-immunoprecipitation of PEX11β and DRP1 in HeLa cells co-expressing 3×Flag-PEX11β and DRP1-GFP. c, Immunoblotting of PMP70 in HeLa cells treated with 200 nM RSL3 or 25 µM erastin for the indicated times. d,e, Confocal images (d) and flow-cytometric analysis (e) of peroxisomal ROS in HeLa cells expressing HyPer7-PTS1, treated as in a. f,g, Peroxisomal morphology in HeLa cells expressing sgNC or DRP1-targeting sgRNAs (f), or shNC or FIS1-targeting shRNAs (g), after 200 nM RSL3 for 4 h. h, Flow-cytometric fluorescence ratios and cell viability in HeLa cells expressing HyPer7-DAAO-PTS1 after 4-h preincubation with D- or L-alanine, with or without 0.5-h pretreatment with 10 µM Fer-1, before 4-h treatment with 200 nM RSL3. i, Immunoblotting of ACOX1, Catalase, AGPS and GNPAT in HeLa cells expressing shNC or MFF-targeting shRNAs. j,k, Immunoblotting and cell death in HeLa cells expressing sgNC or sgRNAs targeting ACOX1 (j) or CAT (k) after vehicle, 100 nM RSL3 for 24 h, or RSL3 after Lip-1 pretreatment. l, qPCR analysis of ACOX1 and CAT mRNA level in CRISPR Ctrl and MFF KO HeLa cells. m, Relative PPARα luciferase activity in HeLa cells expressing sgNC or sgRNAs targeting MFF or PEX11β. n,o, Relative mRNA levels of ACOX1 and CAT (n) and cell death (o) in CRISPR Ctrl and MFF KO cells transfected with PPARα-targeting siRNAs; in o, cells were treated with vehicle, 150 nM RSL3 for 24 h, or RSL3 after Lip-1 pretreatment. p, NRF2 nuclear accumulation in HeLa cells expressing HyPer7-DAAO-PTS1 after D- or L-alanine preincubation for 4 h. GAPDH and Lamin A/C mark cytoplasmic and nuclear fractions, respectively. q, Catalase immunoblotting in cells treated as in p. Scale bars, 5 µm (a,d,f,g). n = 3 biological replicates (e,h,j-o) and 14 cells (a). Data are mean ± s.d. (e,h,j-o) or mean ± s.e.m. (a), analyzed by two-sided Student’s t-tests (l), one-way ANOVA (a,e,h,m,n) or two-way ANOVA (h,j,k,o). NS, not significant.

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Extended Data Fig. 5 17-HETE promotes ferroptosis through MFF-mediated mitochondrial and peroxisomal function.

a, Fluorescence images of CRISPR Ctrl, MFF KO or MFF-rescued HeLa cells, with or without ρ0 induction, stained with TMRE and Hoechst. Scale bars, 10 µm. b, Immunoblotting of MFF and PEX5 in indicated MFF backgrounds, with or without PEX5 knockout. c, Immunoblotting and cell death in untreated HeLa cells or ρ0 cells with siRNA-mediated PEX5 knockdown after treatment with vehicle or 150 nM RSL3 for 24 h, with or without Lip-1 pretreatment. d–f, ATP levels (d), OCR responses (e) and ETC complex I–V activities (f) in CRISPR Ctrl or MFF KO cells after RSL3 treatment; cells were treated with 200 nM RSL3 for 6 h in d and f, with or without Lip-1 pretreatment, or 1 µM RSL3 for 24 h in e. g, Streptavidin blotting of PMP70 and TOM20 in miniTurbo–TOM20–HA-expressing HeLa cells after 200 nM RSL3 for the indicated times. h, Peroxisomal ROS in untreated or ρ0 cells and mitochondrial ROS in wild-type or PEX5-deficient cells after 200 nM RSL3 for 60 min, with or without Lip-1 pretreatment. i, Cytosolic mtDNA levels in wild-type or MFF KO HeLa cells after 200 nM RSL3 addition at 0 min. The red arrow indicates the time point showing a significant difference. j, Cytosolic mtDNA levels in MFF KO HeLa cells with stable MFN1 or MFN2 knockout after 200 nM RSL3 for 6 h, with or without 0.5-h pretreatment with 2 µM Lip-1. k, Cytosolic mtDNA levels in HeLa cells treated with 200 nM RSL3 for 6 h and cell death in HeLa cells treated with 150 nM RSL3 for 24 h after 0.5-h pretreatment with the indicated pharmacological inhibitors. l, Cytosolic mtDNA levels in HeLa cells treated with or without 200 nM RSL3 for 6 h; the inset shows mtDNA primer positions and the dashed arrow indicates mtDNA release. m, VDAC1 oligomerization in CRISPR Ctrl, MFF KO, and DRP1 KO HeLa cells treated with vehicle or 200 nM RSL3 for 6 h, with Lip-1 pretreatment where indicated, followed by EGS crosslinking. n,o, VDAC1 oligomerization (n) and cytosolic mtDNA levels (o) in HeLa cells treated with 200 nM RSL3, 10 µM Mito-TEMPO or both for 6 h. p, Immunoblotting of cGAS–STING pathway activation in CRISPR Ctrl or MFF KO cells treated with or without 200 nM RSL3 for 6 h. q, Immunoblotting and cell death in HeLa cells expressing sgNC or sgRNAs targeting cGAS or STING after 150 nM RSL3 for 24 h, with or without Lip-1 pretreatment. r, Hierarchical clustering of eicosanoid metabolomics data from CRISPR Ctrl or MFF KO cells after 200 nM RSL3 for 6 h. s, Mitochondrial and peroxisomal ROS and cytosolic mtDNA levels in CRISPR Ctrl or MFF KO HeLa cells preincubated with vehicle or 2 µM 17-HETE for 4 h, followed by vehicle or 150 nM RSL3 for 6 h. t, PCA of untargeted metabolomics data from HeLa cells treated with vehicle, 17-HETE, RSL3 or their combination. u, Immunoblotting of CYP4A11, CYP4F2, CYP4F3 and CYP4F11 in HeLa cells treated with vehicle, 25 µM erastin for 24 h or 200 nM RSL3 for 6 h. v, Immunoblotting and cell death in HeLa cells expressing sgNC or CYP4A11-targeting sgRNAs after vehicle or 150 nM RSL3 for 24 h, with or without Lip-1 pretreatment. w, Cell death in CRISPR Ctrl or MFF KO cells with or without CYP4A11 overexpression after 100 nM RSL3 for 24 h, with or without Lip-1 pretreatment. x, Representative images of mitochondrial morphology in CRISPR Ctrl and MFF-KO cells expressing CYP4A11-targeting sgRNAs after treatment with vehicle, 200 nM RSL3 or 2 µM 17-HETE for 4 h. Scale bars, 5 µm. y, Cell death in HeLa cells expressing sgNC or CYP4A11-targeting sgRNAs. Cells were pretreated with vehicle or 2 µM 17-HETE for 4 h, followed by treatment with vehicle, 150 nM RSL3 or 150 nM RSL3 plus 2 µM Lip-1 for an additional 24 h. z, Targeted eicosanoid metabolomics analysis measuring endogenous 17-HETE levels in HeLa cells expressing sgNC or CYP4A11-targeting sgRNAs after exposure to 200 nM RSL3 for 6 h. n = 3 biological replicates (c-f,h-l,o,q,s,v,w,y) and 6 independent samples (z). Data are mean ± s.d., analyzed by two-sided Student’s t-tests (z), one-way ANOVA (k,o) or two-way ANOVA (c,d,f,h-j,l,q,s,v,w,y). NS, not significant. Schematic in l created in BioRender; Dai, X. https://biorender.com/8vlxn8n (2026).

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Extended Data Fig. 6 MFF Ser155 phosphorylation specifically senses and promotes ferroptosis.

a, Schematic of MFF protein structure highlighting Ser155. b, Immunoblotting of total and Ser155-phosphorylated MFF in CRISPR Ctrl or MFF KO HeLa cells stably expressing vector, wild-type MFF, S155A or S155D. c–f, Immunoblotting of MFF Ser155 phosphorylation in HeLa cells treated for the indicated times with 600 nM STS (c), 50 ng/mL TNFα + 1.25 µg/mL CHX (d), 50 ng/mL TNFα + 1.25 µg/mL CHX + 10 µM zVAD (e), or 125 ng/mL TRAIL + 3.125 µg/mL CHX + 50 µM zVAD (f). g,h, Immunoblotting of MFF Ser155 phosphorylation in mouse cardiac ischemia/reperfusion injury (g) and high-fat, high-cholesterol diet-induced fatty liver disease (h) models. i, Cell death in MFF KO HeLa cells expressing different MFF constructs after 24-h treatment with organic peroxides, including 20 µM TBHP, 10 µM CHP or 50 µM BPO, with or without 2 µM Lip-1 pretreatment for 0.5 h. j,k, Viability of MFF KO HeLa cells expressing different MFF constructs after 24-h treatment with the indicated concentrations of STS or TNFα + CHX (j), or TNFα + CHX+zVAD or TRAIL + CHX+zVAD (k). n = 3 (i) and 4 (j,k) biological replicates. Data are mean ± s.d., analyzed by two-way ANOVA. NS, not significant.

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Extended Data Fig. 7 Development of MFF-SPARK.

a, Sequence alignment of the MFF Ser155 phosphorylation site across indicated species. b, Representative fluorescence images of HEK293T cells expressing MFFS155/S155A (WT/mut)-SPARK with different phosphoamino acid-binding domains, treated with or without 500 nM RSL3 for 1 h. c, Quantification of MFFS155/S155A (WT/mut)-SPARK fluorescence intensity in HEK293T cells expressing different phosphoamino acid-binding domains, with or without 500 nM RSL3 for 1 h. d, Dose–response curve of MFF-SPARK activation by RSL3. e, Fluorescence images of MFFS155/S155A (WT/mut)-SPARK in wild-type and GPX4 KO HEK293T cells, with or without Trolox withdrawal. f, Responses of MFFS155-SPARK and MFFS155A mut-SPARK to RSL3 treatment in HeLa, HepG2, and U-2 OS cell lines. Cells were treated with or without 500 nM RSL3 for 1 h. g–n, Normalized MFF-SPARK signal plotted against time after treatment with ferroptosis inducers: 5 µM ML162 (g), 25 µM erastin (h), 5 µM FINO2 (i) or 1 mM FAC (j); apoptosis inducers: 500 nM STS (k) or 100 ng/mL TNFα + 2.5 µg/mL CHX (l); or necroptosis inducers: 100 ng/mL TNFα (m) or 100 ng/mL TRAIL (n), each combined with 2.5 µg/mL CHX and 20 µM zVAD. Scale bars, 10 µm (b,e,f). Maximum responses are shown on the right, respectively. n = 16 (c), 6 (d), 5 (g-n) representative fields. Data are mean ± s.e.m. (c,d,g–n), analyzed by two-sided Student’s t-tests (g–n) or two-way ANOVA (c). NS, not significant.

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Extended Data Fig. 8 MFF-SPARK screening identifies PKCβ-mediated MFF phosphorylation in ferroptosis.

a, Predicted kinases for MFF Ser155 phosphorylation determined using NetPhos. b, Immunoblotting of MFF Ser155 phosphorylation in HeLa cells treated with RSL3 plus ferroptosis inhibitors or kinase inhibitors. c,d, Time-lapse images (c) and normalized MFF-SPARK signals (d) in HEK293T cells expressing MFFS155/S155A (WT/mut)-SPARK after 50 ng/mL PMA at 0 min and 10 µM Go 6983 at 36 min. Scale bars, 10 µm. e, Immunoblotting of MFF Ser155 phosphorylation in HeLa cells after 50 ng/mL PMA for the indicated times. f,g, Immunoblotting of MFF Ser155 phosphorylation in HeLa cells treated with 200 nM RSL3 for 6 h (f) or 25 µM erastin for 24 h (g), together with ferroptosis or PKC inhibitors. h, Fluorescence images and quantification of MFF-SPARK responses in HEK293T cells overexpressing wild-type PKCβ or kinase-dead PKCβ-K371R, treated with vehicle, 200 nM RSL3 for 1 h, or RSL3 after 2 µM Lip-1 pretreatment for 0.5 h. Scale bars, 10 µm. i, Immunoprecipitation of endogenous and phospho-Ser/Thr PKCβ from HeLa cells treated with 25 µM erastin for 24 h or 200 nM RSL3 for 4 h. j,k, Immunoblotting of MFF phosphorylation after 200 nM RSL3 for 4 h in wild-type versus PKCβ-overexpressing HeLa cells (j), and in HeLa cells overexpressing wild-type or kinase-dead PKCβ (k). l, Cell death after 150 nM RSL3 for 24 h and lipid peroxidation after 200 nM RSL3 for 6 h in HeLa cells pretreated with 5 µM Go 6983 or Go 6850 for 0.5 h. m, Immunoblotting of PKCβ in HeLa or HT-1080 cells expressing sgNC or PKCβ-targeting sgRNAs. n,o, Cell death and lipid peroxidation in HeLa (n) or HT-1080 (o) cells expressing sgNC or PKCβ-targeting sgRNAs after RSL3 treatment, with or without Lip-1 as indicated. p,q, Cell death (p) and lipid peroxidation (q) in wild-type or MFF KO HeLa cells expressing PKCβ-targeting sgRNAs and reconstituted with wild-type or K371R PKCβ after 150 nM RSL3 for 24 h (p) or 200 nM RSL3 for 6 h (q), with or without Lip-1 as indicated. r, Lipid peroxidation in MFF/PKCβ DKO cells reconstituted with wild-type or K371R PKCβ and wild-type or S155A MFF, treated as in q. n = 3 biological replicates (l,n-r) and 5 (d), 10 (h) representative fields. Data are mean ± s.d. (l,n-r) or mean ± s.e.m. (d,h), analyzed by two-way ANOVA (h,l,n-r). NS, not significant.

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Extended Data Fig. 9 MFF-SPARK screening identifies DUSP22 as the phosphatase of MFF at Ser155.

a, Co-immunoprecipitation of MFF and DUSP22 in HeLa cells co-expressing 3×Flag-MFF and HA-DUSP22. b, GST pull-down of His-MFF by purified GST–DUSP22 or GST alone after in vitro incubation; bound His-MFF was detected by anti-His immunoblotting. c, Immunoblotting showing dose-dependent reduction of RSL3-induced MFF Ser155 phosphorylation by DUSP22 overexpression. d, Fluorescence images and quantification of MFFS155/S155A (WT/mut)-SPARK treated with or without 20 µM BML-260 for 6 h. Scale bars, 10 µm. e, Immunoblotting of MFF phosphorylation in HeLa cells expressing empty vector, wild-type DUSP22 or phosphatase-dead DUSP22-C88S after 200 nM RSL3 for 6 h. f, Immunoblotting of DUSP22 in HeLa cells expressing sgNC or DUSP22-targeting sgRNAs. g, Cell death and lipid peroxidation in HeLa cells expressing sgNC or DUSP22-targeting sgRNAs. Cells were treated with 100 nM RSL3 for 24 h for cell death analysis, or 150 nM RSL3 for 6 h for lipid peroxidation analysis, with or without Lip-1 pretreatment. h, Lipid peroxidation in wild-type or MFF KO HeLa cells expressing DUSP22-targeting sgRNAs after 150 nM RSL3 for 6 h, with or without Lip-1 pretreatment. i, Lipid peroxidation in MFF/DUSP22 DKO cells reconstituted with wild-type or S155A MFF, treated as in h. n = 3 biological replicates (g-i) and 10 representative fields (d). Data are mean ± s.d. (g–i) or mean ± s.e.m. (d), analyzed by two-way ANOVA. NS, not significant.

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Extended Data Fig. 10 Avermectin B1 enhances MFF-mediated organelle fission and potentiates tumour susceptibility to ferroptosis.

a, Cell death in HeLa cells treated with vehicle, 100 nM RSL3, 10 µM indicated drug or the corresponding combination for 24 h. b, Immunoblotting of MFF Ser155 phosphorylation in HeLa cells treated with 10 μM Avermectin B1 for the indicated time. c,d, Confocal images of mitochondrial morphology in MitoTracker Red- and Hoechst-stained wild-type or MFF KO HeLa cells (c) and peroxisomal morphology in GFP-PTS1-expressing wild-type or MFF KO HeLa cells (d) after 10 µM AVM B1 for 12 h. Dashed boxes outline individual cells in d. Scale bars, 5 µm. e, Lipid peroxidation in wild-type or MFF KO HeLa cells treated with vehicle, 10 µM AVM B1, 150 nM RSL3 or their combination for 6 h, with or without 2 µM Lip-1 pretreatment for 0.5 h. f, Immunoblotting of pull-down assays using a biotin-conjugated AVM B1 derivative in lysates from HeLa cells overexpressing PKCβ, MFF, FSP1, SLC7A11, GPX4 or DUSP22. *, nonspecific bands. g, Lipid peroxidation in HeLa cells expressing sgNC or PKCβ-targeting sgRNA, treated as in e. h, Cell death in HeLa cells treated with vehicle or 100 nM RSL3 for 24 h, and lipid peroxidation in cells treated with vehicle or 150 nM RSL3 for 6 h, with or without 0.5-h pretreatment with 10 µM AVM B1, 5 µM Go 6983, or both. i, Images of HCT-116 xenograft tumours collected after the final tumour-volume measurement. j,k, Body weight of tumour-bearing mice (j) or C57BL/6 mice (k) under the indicated treatments over time. l-n, Major organ weight (l), serum biochemical parameters (m) and histopathological examination of major organs (n) in C57BL/6 mice after AVM B1 treatment. Scale bars, 100 µm (n). o, Model of the 17-HETE-PKCβ-DUSP22-MFF axis coordinating mitochondrial and peroxisomal dysfunction during ferroptosis. n = 3 biological replicates (a,e,g,h), 7 mice (j) and 6 mice (k-m). Data are mean ± s.d. (a,e,g,h) or mean ± s.e.m. (j-m), analyzed by two-sided Student’s t-tests (l,m) or two-way ANOVA (a,e,g,h,j,k). NS, not significant. Schematic in o created in BioRender; Dai, S. https://biorender.com/exhvkgb (2026).

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Uncropped western blot and gel source data.

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Supplementary Fig. 2 (download PDF )

Gating strategies for flow cytometry analysis. a, Gating strategy for percentage-based analyses. Cells were sequentially gated for viable cells (P1, FSC-H versus SSC-H) and singlets (P2, FSC-A versus FSC-H), and the positive population (M3) was defined by fluorescence intensity. Used for cell death analysis by PI staining (Figs. 1e,g,k,l, 2c,f,o, 3g,h, 4h,l,m and 5g,k and Extended Data Figs. 2d,e,y, 4j,k,o, 5c,k,q,v,w,y, 6i, 8l,n–p, 9g and 10a,h), cell death time-course by SYTOX Green (Extended Data Fig. 3k), lipid peroxidation by C11-BODIPY (Figs. 3g,h and 5o and Extended Data Figs. 2l,o,s,u–w,y, 3k, 8l,n–o,q,r, 9g–i and 10e,g,h), intracellular ROS by DCFH-DA (Extended Data Fig. 2n), and mitochondrial membrane potential by TMRE (Extended Data Fig. 3k). b, Gating strategy for MFI-based analyses. Cells were gated for viable cells (P1) and singlets (P2) as in a; MFI was quantified on P2-gated singlets. Used for mitochondrial ROS by MitoSOX (Figs. 2b,j, 3i and 5e and Extended Data Figs. 3i–k and 5h,s), peroxisomal ROS by HyPer7-PTS1 (Figs. 2e,k, 3j and 5f and Extended Data Figs. 4e and 5h,s), mitochondrial H2O2 by mito-HyPer7-DAAO (Extended Data Fig. 3l), and peroxisomal H2O2 by HyPer7-DAAO-PTS1 (Extended Data Fig. 4h).

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Dai, S., Dai, X., Zhang, T. et al. Mitochondrial fission factor senses and governs ferroptosis. Nature (2026). https://doi.org/10.1038/s41586-026-11020-6

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