Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Mosaic composition of RIP1–RIP3 signalling hub and its role in regulating cell death

Nature Cell Biology volume 24, pages 471–482 (2022)Cite this article

Subjects

Abstract

RIP1 and RIP3, cell death mediators, form fibrous amyloids. How RIP1/RIP3 amyloidal oligomers assemble functional necrosomes and control cell death is largely unknown. Here we use super-resolution microscopy to directly visualize cellular necrosomes as mosaics of RIP1 and RIP3 oligomers. The small (initial) mosaic complexes are round, and the large mosaics are in a rod shape. RIP3 oligomers with sizes of tetramer or above are the domains in mosaics that allow MLKL, recruited by phosphorylated RIP3, to oligomerize for necroptosis. Unexpectedly, RIP1 autophosphorylation not only controls the ordered oligomerization of RIP1 but also is required for RIP1-initiated RIP3 homo-oligomerization in correct organization, which is indispensable for the formation of functional rod-shaped mosaics. Similarly, apoptosis initiated by enzymatically defective RIP3 requires the formation of rod-shaped mosaics of RIP3 and RIP1 oligomers. The revealing of nanoscale architecture of necrosomes here innovates our understanding of the structural and organizational basis of this signalling hub in cell death.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Nanoscale imaging analysis of necrosomes in necroptotic cells.
Fig. 2: RIP1–RIP3 mosaics are functional necrosomes.
Fig. 3: RHIM-dependent RIP3 oligomerization is required for MLKL oligomerization but dispensable for phosphorylation of RIP3 and MLKL.
Fig. 4: RIP3 oligomers with sizes of tetramer or above enable phosphorylated MLKL to form oligomers and subsequently trigger cell necroptosis.
Fig. 5: RIP1 kinase activity is required for RIP1 and RIP3 oligomerization in proper configuration that leads to the formation of functional rod-shaped complexes.
Fig. 6: RIP3 autophosphorylation is dispensable for the formation of rod-shaped complex.
Fig. 7: Apoptosis triggered by RIP3 kinase inhibition relies on the mosaic structure composed of RIP1 oligomer.

Similar content being viewed by others

Data availability

The published structures of RIP1–RIP3 hetero-amyloid core (PDB 5V7Z), RIP1 kinase domain (PDB 4NEU), RIP1 death domain (PDB 6AC5) and RIP3 kinase domain (PDB 4M66) are accessible in the PDB (https://www.rcsb.org/) with respective IDs. Numerical source data giving rise to graphical representations and unprocessed images of blots are shown in source data figures. Detailed experimental procedures and additional data supporting the findings of this study are available from the corresponding author on reasonable request. Source data are provided with this paper.

Code availability

All Python scripts and Fiji macros for STORM image analysis are available in the online repository GitHub (https://github.com/xchenxmu/STORMing-the-necrosome).

References

  1. Weinlich, R., Oberst, A., Beere, H. M. & Green, D. R. Necroptosis in development, inflammation and disease. Nat. Rev. Mol. Cell Bio 18, 127–136 (2017).

    Article  CAS  Google Scholar 

  2. Wang, L., Du, F. H. & Wang, X. D. TNF-α induces two distinct caspase-8 activation pathways. Cell 133, 693–703 (2008).

    Article  CAS  PubMed  Google Scholar 

  3. Wilson, N. S., Dixit, V. & Ashkenazi, A. Death receptor signal transducers: nodes of coordination in immune signaling networks. Nat. Immunol. 10, 348–355 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Zhang, D. W. et al. RIP3, an energy metabolism regulator that switches TNF-induced cell death from apoptosis to necrosis. Science 325, 332–336 (2009).

    Article  CAS  PubMed  Google Scholar 

  5. He, S. D. et al. Receptor interacting protein kinase-3 determines cellular necrotic response to TNF-α. Cell 137, 1100–1111 (2009).

    Article  CAS  PubMed  Google Scholar 

  6. Cho, Y. et al. Phosphorylation-driven assembly of the RIP1–RIP3 complex regulates programmed necrosis and virus-induced inflammation. Cell 137, 1112–1123 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Yang, Z. H. et al. A non-canonical PDK1-RSK signal diminishes pro-caspase-8-mediated necroptosis blockade. Mol. Cell 80, 296 (2020).

    Article  CAS  PubMed  Google Scholar 

  8. Sun, L. et al. Mixed lineage kinase domain-like protein mediates necrosis signaling downstream of RIP3 kinase. Cell 148, 213–227 (2012).

    Article  CAS  PubMed  Google Scholar 

  9. Zhao, J. et al. Mixed lineage kinase domain-like is a key receptor interacting protein 3 downstream component of TNF-induced necrosis. Proc. Natl Acad. Sci. USA 109, 5322–5327 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Chen, X. et al. Translocation of mixed lineage kinase domain-like protein to plasma membrane leads to necrotic cell death. Cell Res. 24, 105 (2014).

    Article  CAS  PubMed  Google Scholar 

  11. Cai, Z. Y. et al. Plasma membrane translocation of trimerized MLKL protein is required for TNF-induced necroptosis. Nat. Cell Biol. 16, 200 (2014).

    Article  CAS  Google Scholar 

  12. Wang, H. et al. Mixed lineage kinase domain-like protein MLKL causes necrotic membrane disruption upon phosphorylation by RIP3. Mol. Cell 54, 133–146 (2014).

    Article  CAS  PubMed  Google Scholar 

  13. Dondelinger, Y. et al. MLKL compromises plasma membrane integrity by binding to phosphatidylinositol phosphates. Cell Rep. 7, 971–981 (2014).

    Article  CAS  PubMed  Google Scholar 

  14. Degterev, A. et al. Chemical inhibitor of nonapoptotic cell death with therapeutic potential for ischemic brain injury. Nat. Chem. Biol. 1, 112–119 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Degterev, A. et al. Identification of RIP1 kinase as a specific cellular target of necrostatins. Nat. Chem. Biol. 4, 313–321 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hitomi, J. I. et al. Identification of a molecular signaling network that regulates a cellular necrotic cell death pathway. Cell 135, 1311–1323 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Holler, N. et al. Fas triggers an alternative, caspase-8-independent cell death pathway using the kinase RIP as effector molecule. Nat. Immunol. 1, 489–495 (2000).

    Article  CAS  PubMed  Google Scholar 

  18. Sun, X. Q., Yin, J. P., Starovasnik, M. A., Fairbrother, W. J. & Dixit, V. M. Identification of a novel homotypic interaction motif required for the phosphorylation of receptor-interacting protein (RIP) by RIP3. J. Biol. Chem. 277, 9505–9511 (2002).

    Article  CAS  PubMed  Google Scholar 

  19. Chen, W. Z. et al. Diverse sequence determinants control human and mouse receptor interacting protein 3 (RIP3) and mixed lineage kinase domain-like (MLKL) interaction in necroptotic signaling. J. Biol. Chem. 288, 16247–16261 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hildebrand, J. M. et al. Activation of the pseudokinase MLKL unleashes the four-helix bundle domain to induce membrane localization and necroptotic cell death. Proc. Natl Acad. Sci. USA 111, 15072–15077 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Petrie, E. J. et al. Conformational switching of the pseudokinase domain promotes human MLKL tetramerization and cell death by necroptosis. Nat. Commun. 9, 2422 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Mandal, P. et al. RIP3 induces apoptosis independent of pronecrotic kinase activity. Mol. Cell 56, 481–495 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Newton, K. et al. Activity of protein kinase RIPK3 determines whether cells die by necroptosis or apoptosis. Science 343, 1357–1360 (2014).

    Article  CAS  PubMed  Google Scholar 

  24. Li, J. et al. The RIP1/RIP3 necrosome forms a functional amyloid signaling complex required for programmed necrosis. Cell 150, 339–350 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Mompeán, M. et al. The structure of the necrosome RIPK1–RIPK3 core, a human hetero-amyloid signaling complex. Cell 173, 1244–1253.e1210 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  26. Xie, T. et al. Structural insights into RIP3-mediated necroptotic signaling. Cell Rep. 5, 70–78 (2013).

    Article  CAS  PubMed  Google Scholar 

  27. Murphy, J. M. et al. The pseudokinase MLKL mediates necroptosis via a molecular switch mechanism. Immunity 39, 443–453 (2013).

    Article  CAS  PubMed  Google Scholar 

  28. Rust, M. J., Bates, M. & Zhuang, X. W. Sub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM). Nat. Methods 3, 793–795 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Huang, B., Wang, W. Q., Bates, M. & Zhuang, X. W. Three-dimensional super-resolution imaging by stochastic optical reconstruction microscopy. Science 319, 810–813 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Sigal, Y. M., Zhou, R. B. & Zhuang, X. W. Visualizing and discovering cellular structures with super-resolution microscopy. Science 361, 880–887 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Malkusch, S. & Heilemann, M. Extracting quantitative information from single-molecule super-resolution imaging data with LAMA—LocAlization Microscopy Analyzer. Sci. Rep. 6, 34486 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Berg, S. et al. ilastik: interactive machine learning for (bio) image analysis. Nat. Methods 16, 1226–1232 (2019).

    Article  CAS  PubMed  Google Scholar 

  33. Bates, M., Huang, B., Dempsey, G. T. & Zhuang, X. W. Multicolor super-resolution imaging with photo-switchable fluorescent probes. Science 317, 1749–1753 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wu, X. N. et al. Distinct roles of RIP1–RIP3 hetero- and RIP3–RIP3 homo-interaction in mediating necroptosis. Cell Death Differ. 21, 1709–1720 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Muthuswamy, S. K., Gilman, M. & Brugge, J. S. Controlled dimerization of ErbB receptors provides evidence for differential signaling by homo- and heterodimers. Mol. Cell. Biol. 19, 6845–6857 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Clackson, T. et al. Redesigning an FKBP–ligand interface to generate chemical dimerizers with novel specificity. Proc. Natl Acad. Sci. USA 95, 10437–10442 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Inobe, T. & Nukina, N. Rapamycin-induced oligomer formation system of FRB-FKBP fusion proteins. J. Biosci. Bioeng. 122, 40–46 (2016).

    Article  CAS  PubMed  Google Scholar 

  38. Zhang, Y. et al. RIP1 autophosphorylation is promoted by mitochondrial ROS and is essential for RIP3 recruitment into necrosome. Nat. Commun. 8, 14329 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Li, J. X. et al. The B-RafV600E inhibitor dabrafenib selectively inhibits RIP3 and alleviates acetaminophen-induced liver injury. Cell Death Dis. 5, e1278 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Chen, W. Z. et al. Ppm1b negatively regulates necroptosis through dephosphorylating Rip3. Nat. Cell Biol. 17, 434 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Harris, P. A. et al. Discovery of small molecule RIP1 kinase inhibitors for the treatment of pathologies associated with necroptosis. ACS Med. Chem. Lett. 4, 1238–1243 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ding, J. J. et al. Structural and functional insights into host death domains inactivation by the bacterial arginine GlcNAcyltransferase effector. Mol. Cell 74, 922 (2019).

    Article  CAS  PubMed  Google Scholar 

  43. Dannappel, M. et al. RIPK1 maintains epithelial homeostasis by inhibiting apoptosis and necroptosis. Nature 513, 90 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Dillon, C. P. et al. RIPK1 blocks early postnatal lethality mediated by caspase-8 and RIPK3. Cell 157, 1189–1202 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Kaiser, W. J. et al. RIP1 suppresses innate immune necrotic as well as apoptotic cell death during mammalian parturition. Proc. Natl Acad. Sci. USA 111, 7753–7758 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Orozco, S. et al. RIPK1 both positively and negatively regulates RIPK3 oligomerization and necroptosis. Cell Death Differ. 21, 1511–1521 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rickard, J. A. et al. RIPK1 regulates RIPK3-MLKL-driven systemic inflammation and emergency hematopoiesis. Cell 157, 1175–1188 (2014).

    Article  CAS  PubMed  Google Scholar 

  48. Roderick, J. E. et al. Hematopoietic RIPK1 deficiency results in bone marrow failure caused by apoptosis and RIPK3-mediated necroptosis. Proc. Natl Acad. Sci. USA 111, 14436–14441 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wu, X. L. et al. The amyloid structure of mouse RIPK3 (receptor interacting protein kinase 3) in cell necroptosis. Nat. Commun. 12, 1627 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Meng, H. Y. et al. Death-domain dimerization-mediated activation of RIPK1 controls necroptosis and RIPK1-dependent apoptosis. Proc. Natl Acad. Sci. USA 115, E2001–E2009 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Jaco, I. et al. MK2 phosphorylates RIPK1 to prevent TNF-induced cell death. Mol. Cell 66, 698 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Dondelinger, Y. et al. MK2 phosphorylation of RIPK1 regulates TNF-mediated cell death. Nat. Cell Biol. 19, 1237–1247 (2017).

    Article  CAS  PubMed  Google Scholar 

  53. Geng, J. F. et al. Regulation of RIPK1 activation by TAK1-mediated phosphorylation dictates apoptosis and necroptosis. Nat. Commun. 8, 359 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Meng, Y. X., Sandow, J. J., Czabotar, P. E. & Murphy, J. M. The regulation of necroptosis by post-translational modifications. Cell Death Differ. 28, 861–883 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Huang, Z. et al. RIP1/RIP3 binding to HSV-1 ICP6 initiates necroptosis to restrict virus propagation in mice. Cell Host Microbe 17, 229–242 (2015).

    Article  CAS  PubMed  Google Scholar 

  56. Yang, J. Y. et al. Improved protein structure prediction using predicted interresidue orientations. Proc. Natl Acad. Sci. USA 117, 1496–1503 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (81788101, 31420103910 and 81630042 to J.H.; 31871386, 31501115 and 32070736 to X.C.; 12090052 and 11874310 to J.S.), National Key R&D Program of China (2020YFA0803500 to J.H.), the 111 Project (B12001 to J.H.), the CAMS Innovation Fund for Medical Science (2019-I2M-5-062 to J.H.) and the China Postdoctoral Science Foundation (2016T90598 to X.C.). We thank L. Yao and C. Wu for help with electron microscopy; Q. Liu and Y. Fan (Bruker) for their assistance with confocal microscopy and AFM, respectively. We also acknowledge C. Zhou and L. Wang from Nikon for support and helpful discussions on super-resolution imaging.

Author information

Authors and Affiliations

  1. State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Biology, School of Life Sciences, Xiamen University, Xiamen, China

    Xin Chen, Rongfeng Zhu, Wenxin Wang, Yating Cao, Hanyi Cai & Jiahuai Han

  2. Department of Physics and Fujian Provincial Key Laboratory for Soft Functional Materials Research, Xiamen University, Xiamen, China

    Jinjin Zhong, Yongfa Ying, Xiang Li & Jianwei Shuai

  3. National Institute for Data Science in Health and Medicine, Xiamen, China

    Jianwei Shuai & Jiahuai Han

  4. Research Unit of Cellular Stress of CAMS, Cancer Research Center of Xiamen University, Xiang’an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China

    Jiahuai Han

Authors
  1. Xin Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rongfeng Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jinjin Zhong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Yongfa Ying
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Wenxin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yating Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Hanyi Cai
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Xiang Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jianwei Shuai
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jiahuai Han
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

X.C. carried out the majority of experimental work with the help of W.W., Y.C. and H.C. R.Z. performed molecular modelling. J.Z., X.L., Y.Y. and J.S. carried out the analysis of super-resolution images. X.C. and J.H. designed experiments, interpreted data and wrote the manuscript. J.H. conceived and supervised the study.

Corresponding authors

Correspondence to Xin Chen or Jiahuai Han.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks Sang-Hee Shim and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Additional information

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

Extended data

Extended Data Fig. 1 Necrosome is visualized as diffraction-limited puncta growing in the process of cell necroptosis.

a, Confocal images of HA-RIP3 and MLKL-Flag-reconstituted MLKL-KO HeLa cells treated with DMSO or TSZ (T: TNF, 10 ng/ml; S: Smac mimetic (SM-164), 100 nM; Z: zVAD-fmk, 20 μM), fixed and labeled for HA-RIP3 (green), RIP1 (purple) and MLKL-Flag (light blue). Red arrows in magnified images outlined by the white boxes emphasize the growing necrosome puncta. b-d, Intensity distribution of RIP1 (b, n = 39, 232, 453 for TSZ 0, 2, 4 h, respectively), RIP3 (c, n = 59, 940, 1772 for TSZ 0, 2, 4 h, respectively) or MLKL (d, n = 11, 278, 735 for TSZ 0, 2, 4 h, respectively) clusters detected in cells treated as in a. ‘n’ refers to the number of structures analyzed across two independent experiments. Box plots (b-d) show median and 25th to 75th percentiles, and whiskers indicate the minimum and maximum values. P values are determined by Kruskal-Wallis test with Dunn’s multiple comparisons test. Scale bars, 10 μm (original images) and 2 μm (magnified images). Statistical source data are provided in Source Data Extended Data Fig. 1.

Source data

Extended Data Fig. 2 Analysis of single-color STORM images.

a, Representative histogram of localization precision of CF 647 calculated by LAMA algorithm31. b-e, Segmentation analysis of single-color STORM images (b). An example of RIP1 puncta (yellow) identified by machine learning-based algorithm (ilastik) in untreated HeLa cells expressing RIP3 is shown (c). The details of segmentation analysis are described in the Methods section. Area distribution (d) and ellipticity distribution (e) of RIP1 clusters were automatically quantified. Here, r value represents the effective diameter of the square with an equivalent area to the detected signals. The clusters with r value of more than 80 nm are TSZ-induced clusters and among them, those with an ellipticity of more than 2.00 are further regarded as rod-shaped structures. Scale bar, 100 nm. Statistical source data are provided in Source Data Extended Data Fig. 2.

Source data

Extended Data Fig. 3 Rod-shaped structure is a general feature of cellular necrosome.

a, Single-color STORM images of endogenous RIP3 complexes revealed by using an anti-RIP3 antibody. Magnified images outlined by white boxes emphasize the rod-shaped RIP3 complexes only present in WT but not RIP3-deficient HT-29 cells treated with TSZ for 8 h. b, STORM images of RIP1 or RIP3 in HT-29 cells treated with TSZ (T: TNF, 10 ng/ml; S: Smac mimetic (SM-164), 100 nM; Z: zVAD-fmk, 20 μM) for indicated time. Magnified images are shown as inset figures, highlighting the RIP1 or RIP3 clusters during cell necroptosis. c, Percentage of rod-shaped structures detected by RIP1 or RIP3 staining in total enlarged clusters (RIP1, n = 1, 277, 334 for TSZ 0, 4, 8 h, respectively; RIP3, n = 8, 468, 409 for TSZ 0, 4, 8 h, respectively) by TSZ stimulation. The definitions of round- and rod-shaped structures are described in Extended Data Fig. 2d,e. d-g, Width (d) and length (f) distributions of RIP1 stained rods (n = 43, 61 for TSZ 4, 8 h, respectively) or width (e) and length (g) distributions of RIP3 stained rods (n = 76, 105 for TSZ 4, 8 h, respectively) in necroptotic HT-29 cells treated as in b. In c-g, ‘n’ refers to the number of structures analyzed across three independent experiments. Scale bars, 5 μm (original images in a and b) and 100 nm (magnified images in a and b). Statistical source data are provided in Source Data Extended Data Fig. 3.

Source data

Extended Data Fig. 4 Analysis of two-color STORM images.

a, Representative histogram of localization precision of CF 568 calculated by LAMA algorithm31. b, Two-color STORM images of the RIP1-RIP3 necrosomes in HA-RIP3 expressing HeLa cells treated with TSZ, and labeled for RIP1 and RIP3 (top, “both”), only for RIP3 (middle, “anti-HA only”) or only for RIP1 (bottom, “anti-RIP1 only”). Green indicates mouse secondary antibody conjugated CF 568, and purple indicates rabbit secondary antibody conjugated CF 647. Data are representative of four independent experiments. c, Cross-talk percentages between the two STORM color-channels determined from single-color-labeled necrosome shown in b. Data are mean ± SD of biological triplicates. d,e, Analysis workflow of two-color STORM images in this study (d). Clusters identified by ilastik in each channel were further assessed the possibility of co-clustering in a single channel or overlap between two channels. An example of cluster analysis of two-color STORM imaging is shown in e. The details of segmentation/overlap analysis of clusters are described in the Methods section. Scale bars, 200 nm (e) and 100 nm (b). Statistical source data are provided in Source Data Extended Data Fig. 4.

Source data

Extended Data Fig. 5 Two-color STORM imaging of rod-shaped necrosomes.

a, Two-color STORM of necrosomes showing the spatial localization of RIP1-RIP3 in HA-RIP3 and MLKL-Flag-expressing MLKL-KO HeLa cells treated with TSZ. b-d, Viability of HT-29 (b), LS 174 T (c) or THP-1 (d) cells treated as indicated. THP-1 cells were primed by 100 nM PMA. Data are represented as mean ± SD of biological triplicates. e, Two-color STORM images of RIP1 and RIP3 clusters in cells from (b-d). f, Two-color STORM of necrosomes showing the spatial localization of RIP3-MLKL in HA-RIP3 and MLKL-Flag-expressing MLKL-KO HeLa cells treated with TSZ. g-j, Two-color STORM images showing the localizations of pRIP3 (g) or pMLKL (i) and RIP3 in WT and RIP3-deficient (g) or MLKL-deficient (i) HT-29 cells in the presence of TSZ. Area of pRIP3 (n = 163, 90 structures analyzed across three independent experiments for Round or Rod, respectively, h) or pMLKL (n = 237, 237 structures analyzed across three independent experiments for Round or Rod, respectively, j) puncta in round-/rod-shaped necrosome were calculated. STORM images are representative of three independent experiments. Data in h and j are mean ± SEM. All P values are determined by two-tailed, unpaired t-test. Scale bars, 5 μm (original images in g and i) and 100 nm (a, e, f and magnified images in g and i). Statistical source data are provided in Source Data Extended Data Fig. 5.

Source data

Extended Data Fig. 6 RIP1 is dispensable for RIP3 rods formation by overexpressed RIP3 and RIP3 overexpression-induced necroptosis.

a, Single-color STORM image of RIP3 complex by Dox-induced RIP3 in RIP1-deficient HeLa cells (left) and two-color STORM image of TSZ-induced RIP1-RIP3 rod in HA-RIP3 expressing HeLa cells (right). b-f, Flag-RIP3-WT or Flag-RIP3-RHIMMut expression was induced in RIP1-deficient HeLa cells by addition of Dox. The RIP3-containing complex was immunoprecipitated with an anti-Flag antibody and visualized by using negative stain EM (b). Cell viability was measured based on quantitation of the ATP present (c). Data are represented as mean ± SD of biological triplicates. Confocal images of RIP3 are shown (d) and the fraction of cells with RIP3 puncta were calculated (e). n = 75–324 cells pooled by two independent experiments. Cell lysates were collected and analyzed by immunoblotting for the indicated proteins under reducing or non-reducing conditions (f). Scale bars, 10 μm (d) and 100 nm (a and b). Unprocessed blots and statistical source data are provided in Source Data Extended Data Fig. 6.

Source data

Extended Data Fig. 7 Disordered RIP1 complexes by non-phosphorylated RIP1.

a, HA-RIP3-expressing HeLa cells were treated with TSZ or TSZ plus Nec-1. Cell lysates were collected and subjected to western blot analysis for the indicated proteins. b-e, Viability of HA-RIP3 expressing HeLa (b), HT-29 (c), LS 174 T (d) and THP-1 (e) cells treated as indicated. THP-1 cells were primed by 100 nM PMA. Data are represented as mean ± SD of biological triplicates. f,g, Confocal images of RIP1 and RIP3 (f) and area distribution of RIP1 clusters (g, n = 2015 for TSZ and n = 1131 for TSZ + Nec-1) in cells treated as in b. ‘n’ refers to the number of structures analyzed across two independent experiments. h, Flag-RIP1 WT or mutants were overexpressed in RIP1-KO HeLa cells with or without Nec-1 for 24 h. Cell lysates were collected and subjected to western blot analysis for the indicated proteins. i, Confocal images of Flag-RIP1 WT or mutants in cells treated as in h. The experiment was performed twice with similar results. Scale bars, 10 μm. Unprocessed blots and statistical source data are provided in Source Data Extended Data Fig. 7.

Source data

Extended Data Fig. 8 Effect of RIP3 kinase inhibitors on the necrosome formation.

a, Confocal images of the RIP1-RIP3 necrosomes in RIP3-expressing HeLa cells treated with TSZ or TSZ plus RIP3 kinase inhibitors (GSK’840 or Dabra). Purple indicates RIP1 and green is RIP3. b, Area histogram of RIP3 puncta in cells from a. n = 973–3524 clusters from 10 fields. c-f, Flag-RIP3 was co-overexpressed with PPM1B WT or its inactive form (R179G) in HEK293T cells. Cell lysates were collected and subjected to western blot analysis for the indicated proteins. Data are representative of three independent experiments (c). Representative confocal images of RIP3 and PPM1B-WT or PPM1B-R179G from two independent experiments (d). STORM images (e) and length distribution (f) of RIP3 rods in the presence of PPM1B WT or R179G mutant (n = 699 for WT and n = 589 for R179G). ‘n’ refers to the number of structures analyzed across two independent experiments. Box plots show median and 25th to 75th percentiles, and whiskers indicate the minimum and maximum values. P values are determined by two-tailed, unpaired t-test. Scale bars, 10 μm (a and d) and 100 nm (e). Unprocessed blots and statistical source data are provided in Source Data Extended Data Fig. 8.

Source data

Extended Data Fig. 9 The effects of expression of mRIP3 WT or mutants in HEK293T cells.

a-c, Flag-mRIP3 WT or mutants (K51A, D161N, or RHIMMut) were expressed in HEK293T cells with or without 5 μM GSK’872. Confocal (a) and STORM (c) images of RIP1-RIP3 complexes are shown. The fraction of cells with RIP3 puncta in a were calculated (b). n = 97–156 cells pooled by two independent experiments. Data in c are representative of three independent experiments. Scale bars, 10 μm (a) and 100 nm (c). Statistical source data are provided in Source Data Extended Data Fig. 9.

Source data

Extended Data Fig. 10 Model of the assembly and function of mosaic RIP1-RIP3 rods.

a, A hypothetic model of RIP1-RIP3 mosaics: (I) Bidirectional β sheets resulted from RHIM-dependent RIP1/RIP3 homo- or hetero-interactions; (II) The β sheets further form helical necrosome rods with about 47 nm in width and 33 nm in pitch length; (III) RIP1/RIP3 homo-oligomers distribute heterogeneously in the rod-shaped necrosome, exhibiting a mosaic pattern. b, Upon necroptosis stimuli, RIP1 is autophosphorylated and this modification retains RIP1 assembly in a proper manner. Ordered RIP1 interaction initiates ordered recruitment of downstream RIP3, leading to the formation of helical rod-shaped necrosomes. Necrosomal RIP1- and RIP3-homo-oligomers distribute as a mosaic pattern, and RIP3 oligomers with sizes equal to or more than tetramer license phosphorylated MLKL to oligomerize for necroptosis. RHIM domain-mediated interaction rather than RIP3 autophosphorylation/MLKL recruitment is indispensable for the formation of rod-shaped necrosomes. In addition, the mosaic RIP1-RIP3 rods are essential for apoptosis by recruiting FADD/Caspase-8 when RIP3 kinase activity was eliminated by GSK’872 or by kinase-dead mutations. Disrupting the ordered RIP1-RIP3 rod-shaped structures could impair the recruitment/activation of downstream molecules. Thus, the ordered RIP1-RIP3 mosaic rod functions as a bidirectional module for the signaling of necroptosis and apoptosis under certain conditions.

Supplementary information

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 3

Unprocessed western blots.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 4

Unprocessed western blots.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 6

Unprocessed western blots.

Source Data Fig. 7

Statistical source data.

Source Data Fig. 7

Unprocessed western blots.

Source Data Extended Data Fig. 1

Statistical source data.

Source Data Extended Data Fig. 2

Statistical source data.

Source Data Extended Data Fig. 3

Statistical source data.

Source Data Extended Data Fig. 4

Statistical source data.

Source Data Extended Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 6

Statistical source data.

Source Data Extended Data Fig. 6

Unprocessed western blots.

Source Data Extended Data Fig. 7

Statistical source data.

Source Data Extended Data Fig. 7

Unprocessed western blots.

Source Data Extended Data Fig. 8

Statistical source data.

Source Data Extended Data Fig. 8

Unprocessed western blots.

Source Data Extended Data Fig. 9

Statistical source data.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, X., Zhu, R., Zhong, J. et al. Mosaic composition of RIP1–RIP3 signalling hub and its role in regulating cell death. Nat Cell Biol 24, 471–482 (2022). https://doi.org/10.1038/s41556-022-00854-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-022-00854-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing