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.

  • Perspective
  • Published:

Adding intrinsically disordered proteins to biological ageing clocks

Abstract

Research into how the young and old differ, and which biomarkers reflect the diverse biological processes underlying ageing, is a current and fast-growing field. Biological clocks provide a means to evaluate whether a molecule, cell, tissue or even an entire organism is old or young. Here we summarize established and emerging molecular clocks as timepieces. We emphasize that intrinsically disordered proteins (IDPs) tend to transform into a β-sheet-rich aggregated state and accumulate in non-dividing or slowly dividing cells as they age. We hypothesize that understanding these protein-based molecular ageing mechanisms might provide a conceptual pathway to determining a cell’s health age by probing the aggregation state of IDPs, which we term the IDP clock.

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

Access options

Buy this article

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

Fig. 1: The IDP clock.
Fig. 2: Main challenges for reading the IDP clock in vivo.

Similar content being viewed by others

References

  1. Moqri, M. et al. Biomarkers of aging for the identification and evaluation of longevity interventions. Cell 186, 3758–3775 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M. & Kroemer, G. Hallmarks of aging: an expanding universe. Cell 186, 243–278 (2023).

    Article  PubMed  Google Scholar 

  3. Gladyshev, V. N. et al. Molecular damage in aging. Nat. Aging 1, 1096–1106 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Horvath, S. & Raj, K. DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nat. Rev. Genet. 19, 371–384 (2018).

    Article  CAS  PubMed  Google Scholar 

  5. Field, A. E. et al. DNA methylation clocks in aging: categories, causes, and consequences. Mol. Cell 71, 882–895 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Lee, H. Y., Lee, S. D. & Shin, K.-J. Forensic DNA methylation profiling from evidence material for investigative leads. BMB Rep. 49, 359–369 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Jackson, S. H. D., Weale, M. R. & Weale, R. A. Biological age—what is it and can it be measured? Arch. Gerontol. Geriatr. 36, 103–115 (2003).

    Article  PubMed  Google Scholar 

  8. Vaiserman, A. & Krasnienkov, D. Telomere length as a marker of biological age: state-of-the-art, open issues, and future perspectives. Front. Genet. 11, 630186 (2020).

    Article  CAS  PubMed  Google Scholar 

  9. Babu, M. M., Kriwacki, R. W. & Pappu, R. V. Structural biology. Versatility from protein disorder. Science 337, 1460–1461 (2012).

    Article  CAS  PubMed  Google Scholar 

  10. Dyson, H. J. & Wright, P. E. Intrinsically unstructured proteins and their functions. Nat. Rev. Mol. Cell Biol. 6, 197–208 (2005).

    Article  CAS  PubMed  Google Scholar 

  11. Dobson, C. M. Protein misfolding, evolution and disease. Trends Biochem. Sci. 24, 329–332 (1999).

    Article  CAS  PubMed  Google Scholar 

  12. Scheres, S. H. W., Ryskeldi-Falcon, B. & Goedert, M. Molecular pathology of neurodegenerative diseases by cryo-EM of amyloids. Nature 621, 701–710 (2023).

    Article  CAS  PubMed  Google Scholar 

  13. Arseni, D. et al. Structure of pathological TDP-43 filaments from ALS with FTLD. Nature 601, 139–143 (2022).

    Article  CAS  PubMed  Google Scholar 

  14. Chatani, E. & Yamamoto, N. Recent progress on understanding the mechanisms of amyloid nucleation. Biophys. Rev. 10, 527–534 (2018).

    Article  CAS  PubMed  Google Scholar 

  15. Ke, P. C. et al. Half a century of amyloids: past, present and future. Chem. Soc. Rev. 49, 5473–5509 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Dobson, C. M., Knowles, T. P. J. & Vendruscolo, M. The amyloid phenomenon and its significance in biology and medicine. Cold Spring Harb. Perspect. Biol. 12, a033878 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Chiti, F. & Dobson, C. M. Protein misfolding, amyloid formation, and human disease: a summary of progress over the last decade. Annu. Rev. Biochem. 86, 27–68 (2017).

    Article  CAS  PubMed  Google Scholar 

  18. Iadanza, M. G., Jackson, M. P., Hewitt, E. W., Ranson, N. A. & Radford, S. E. A new era for understanding amyloid structures and disease. Nat. Rev. Mol. Cell Biol. 19, 755–773 (2018).

    Article  CAS  PubMed  Google Scholar 

  19. Alberti, S. & Hyman, A. A. Biomolecular condensates at the nexus of cellular stress, protein aggregation disease and ageing. Nat. Rev. Mol. Cell Biol. 22, 196–213 (2021).

    Article  CAS  PubMed  Google Scholar 

  20. Vendruscolo, M. & Fuxreiter, M. Sequence determinants of the aggregation of proteins within condensates generated by liquid-liquid phase separation. J. Mol. Biol. 434, 167201 (2022).

    Article  CAS  PubMed  Google Scholar 

  21. Alberti, S. & Dormann, D. Liquid-liquid phase separation in disease. Annu Rev. Genet 53, 171–194 (2019).

    Article  CAS  PubMed  Google Scholar 

  22. Serio, T. R. et al. Nucleated conformational conversion and the replication of conformational information by a prion determinant. Science 289, 1317–1321 (2000).

    Article  CAS  PubMed  Google Scholar 

  23. Serio, T. R. & Lindquist, S. L. Protein-only inheritance in yeast: something to get [PSI+]-ched about. Trends Cell Biol. 10, 98–105 (2000).

    Article  CAS  PubMed  Google Scholar 

  24. Šarić, A., Chebaro, Y. C., Knowles, T. P. J. & Frenkel, D. Crucial role of non-specific interactions in amyloid nucleation. Proc. Natl Acad. Sci. USA 111, 17869–17874 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Ray, S. et al. Mass photometric detection and quantification of nanoscale α-synuclein phase separation. Nat. Chem. 15, 1306–1316 (2023).

    Article  CAS  PubMed  Google Scholar 

  26. Kar, M. et al. Phase separating RNA binding proteins form heterogeneous distributions of clusters in subsaturated solutions. Proc. Natl Acad. Sci. USA 119, e2202222119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017).

    Article  PubMed  Google Scholar 

  28. Boeynaems, S. et al. Protein phase separation: a new phase in cell biology. Trends Cell Biol. 28, 420–435 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Patel, A. et al. A liquid-to-solid phase transition of the ALS protein FUS accelerated by disease mutation. Cell 162, 1066–1077 (2015).

    Article  CAS  PubMed  Google Scholar 

  30. Zhang, P. et al. Chronic optogenetic induction of stress granules is cytotoxic and reveals the evolution of ALS-FTD pathology. eLife 8, e39578 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Shen, Y. et al. The liquid-to-solid transition of FUS is promoted by the condensate surface. Proc. Natl Acad. Sci. USA 120, e2301366120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Linsenmeier, M. et al. The interface of condensates of the hnRNPA1 low-complexity domain promotes formation of amyloid fibrils. Nat. Chem. 15, 1340–1349 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Emmanouilidis, L. et al. A solid beta-sheet structure is formed at the surface of FUS droplets during aging. Nat. Chem. Biol. https://doi.org/10.1038/s41589-024-01573-w (2024).

    Article  PubMed  Google Scholar 

  34. Lashuel, H. A. Rethinking protein aggregation and drug discovery in neurodegenerative diseases: why we need to embrace complexity? Curr. Opin. Chem. Biol. 64, 67–75 (2021).

    Article  CAS  PubMed  Google Scholar 

  35. Bolognesi, B. et al. The mutational landscape of a prion-like domain. Nat. Commun. 10, 4162 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Labbadia, J. & Morimoto, R. I. The biology of proteostasis in aging and disease. Annu. Rev. Biochem. 84, 435–464 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Hipp, M. S., Kasturi, P. & Hartl, F. U. The proteostasis network and its decline in ageing. Nat. Rev. Mol. Cell Biol. 20, 421–435 (2019).

    Article  CAS  PubMed  Google Scholar 

  38. Patel, A. et al. ATP as a biological hydrotrope. Science 356, 753–756 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Gallotta, I. et al. Extracellular proteostasis prevents aggregation during pathogenic attack. Nature 584, 410–414 (2020).

    Article  CAS  PubMed  Google Scholar 

  40. Rutledge, B. S., Choy, W.-Y. & Duennwald, M. L. Folding or holding?—Hsp70 and Hsp90 chaperoning of misfolded proteins in neurodegenerative disease. J. Biol. Chem. 298, 101905 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Hofweber, M. et al. Phase separation of FUS is suppressed by its nuclear import receptor and arginine methylation. Cell 173, 706–719.e13 (2018).

    Article  CAS  PubMed  Google Scholar 

  42. Yoshizawa, T. et al. Nuclear import receptor inhibits phase separation of FUS through binding to multiple sites. Cell 173, 693–705.e22 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Guo, L. et al. Nuclear-import receptors reverse aberrant phase transitions of rna-binding proteins with prion-like domains. Cell 173, 677–692.e20 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Milles, S. et al. Facilitated aggregation of FG nucleoporins under molecular crowding conditions. EMBO Rep. 14, 178–183 (2013).

    Article  CAS  PubMed  Google Scholar 

  45. Mateju, D. et al. An aberrant phase transition of stress granules triggered by misfolded protein and prevented by chaperone function. EMBO J. 36, 1669–1687 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Bah, A. & Forman-Kay, J. D. Modulation of intrinsically disordered protein function by post-translational modifications. J. Biol. Chem. 291, 6696–6705 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Hofweber, M. & Dormann, D. Friend or foe—Post-translational modifications as regulators of phase separation and RNP granule dynamics. J. Biol. Chem. 294, 7137–7150 (2019).

    Article  CAS  PubMed  Google Scholar 

  48. Simandi, Z. et al. Arginine methyltransferase PRMT8 provides cellular stress tolerance in aging motoneurons. J. Neurosci. 38, 7683–7700 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Das, T. et al. Metastable condensates suppress conversion to amyloid fibrils. Preprint at bioRxiv https://doi.org/10.1101/2024.02.28.582569 (2024).

  50. Mann, J. R. et al. RNA binding antagonizes neurotoxic phase transitions of TDP-43. Neuron 102, 321–338.e8 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Maharana, S. et al. RNA buffers the phase separation behavior of prion-like RNA binding proteins. Science 360, 918–921 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Simonsen, A. & Wollert, T. Don’t forget to be picky – selective autophagy of protein aggregates in neurodegenerative diseases. Curr. Opin. Cell Biol. 75, 102064 (2022).

    Article  CAS  PubMed  Google Scholar 

  53. Adriaenssens, E., Ferrari, L. & Martens, S. Orchestration of selective autophagy by cargo receptors. Curr. Biol. 32, R1357–R1371 (2022).

    Article  CAS  PubMed  Google Scholar 

  54. Noda, N. N., Wang, Z. & Zhang, H. Liquid-liquid phase separation in autophagy. J. Cell Biol. 219, e202004062 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Zhang, Y. et al. SEPA-1 mediates the specific recognition and degradation of P granule components by autophagy in C. elegans. Cell 136, 308–321 (2009).

    Article  CAS  PubMed  Google Scholar 

  56. Yamasaki, A. et al. Liquidity is a critical determinant for selective autophagy of protein condensates. Mol. Cell 77, 1163–1175.e9 (2020).

    Article  CAS  PubMed  Google Scholar 

  57. Wong, Y. C. & Holzbaur, E. L. F. The regulation of autophagosome dynamics by huntingtin and HAP1 is disrupted by expression of mutant huntingtin, leading to defective cargo degradation. J. Neurosci. 34, 1293–1305 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Si, K. Prions: what are they good for? Annu. Rev. Cell Dev. Biol. 31, 149–169 (2015).

    Article  CAS  PubMed  Google Scholar 

  59. Berchowitz, L. E. et al. Regulated formation of an amyloid-like translational repressor governs gametogenesis. Cell 163, 406–418 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Fowler, D. M. et al. Functional amyloid formation within mammalian tissue. PLoS Biol. 4, e6 (2006).

    Article  PubMed  Google Scholar 

  61. Lechler, M. C. et al. Reduced insulin/IGF-1 signaling restores the dynamic properties of key stress granule proteins during aging. Cell Rep. 18, 454–467 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Harel, I. et al. Identification of protein aggregates in the aging vertebrate brain with prion-like and phase separation properties. Preprint at bioRxiv https://doi.org/10.1101/2022.02.26.482115 (2022).

  63. Chen, Y. R. et al. Tissue-specific landscape of protein aggregation and quality control in an aging vertebrate. Preprint at bioRxiv https://doi.org/10.1101/2022.02.26.482120 (2022).

  64. Vecchi, G. et al. Proteome-wide observation of the phenomenon of life on the edge of solubility. Proc. Natl Acad. Sci. USA 117, 1015–1020 (2020).

    Article  CAS  PubMed  Google Scholar 

  65. Hampel, H. et al. Blood-based biomarkers for Alzheimer’s disease: current state and future use in a transformed global healthcare landscape. Neuron 111, 2781–2799 (2023).

    Article  CAS  PubMed  Google Scholar 

  66. Jucker, M. & Walker, L. C. Propagation and spread of pathogenic protein assemblies in neurodegenerative diseases. Nat. Neurosci. 21, 1341–1349 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Privé, G. G. Detergents for the stabilization and crystallization of membrane proteins. Methods 41, 388–397 (2007).

    Article  PubMed  Google Scholar 

  68. Gwosch, K. C. et al. MINFLUX nanoscopy delivers 3D multicolor nanometer resolution in cells. Nat. Methods 17, 217–224 (2020).

    Article  CAS  PubMed  Google Scholar 

  69. Xu, M., Ren, W., Tang, X., Hu, Y. & Zhang, H. Advances in development of fluorescent probes for detecting amyloid-β aggregates. Acta Pharmacol. Sin. 37, 719–730 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Strømland, Ø., Jakubec, M., Furse, S. & Halskau, Ø. Detection of misfolded protein aggregates from a clinical perspective. J. Clin. Transl. Res 2, 11–26 (2016).

    PubMed  PubMed Central  Google Scholar 

  71. Altay, M. F. et al. Development and validation of an expanded antibody toolset that captures alpha-synuclein pathological diversity in Lewy body diseases. NPJ Parkinsons Dis. 9, 161 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Fang, Y.-S. et al. Full-length TDP-43 forms toxic amyloid oligomers that are present in frontotemporal lobar dementia-TDP patients. Nat. Commun. 5, 4824 (2014).

    Article  CAS  PubMed  Google Scholar 

  73. Shuken, S. R. et al. Limited proteolysis–mass spectrometry reveals aging-associated changes in cerebrospinal fluid protein abundances and structures. Nat. Aging 2, 379–388 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Dasari, S. et al. Amyloid typing by mass spectrometry in clinical practice: a comprehensive review of 16,175 samples. Mayo Clin. Proc. 95, 1852–1864 (2020).

    Article  CAS  PubMed  Google Scholar 

  75. Ling, S.-C., Polymenidou, M. & Cleveland, D. W. Converging mechanisms in ALS and FTD: disrupted RNA and protein homeostasis. Neuron 79, 416–438 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Tziortzouda, P., Van Den Bosch, L. & Hirth, F. Triad of TDP43 control in neurodegeneration: autoregulation, localization and aggregation. Nat. Rev. Neurosci. 22, 197–208 (2021).

    Article  CAS  PubMed  Google Scholar 

  77. Partridge, L., Deelen, J. & Slagboom, P. E. Facing up to the global challenges of ageing. Nature 561, 45–56 (2018).

    Article  CAS  PubMed  Google Scholar 

  78. McMahon, M., Forester, C. & Buffenstein, R. Aging through an epitranscriptomic lens. Nat. Aging 1, 335–346 (2021).

    Article  PubMed  Google Scholar 

  79. Galkin, F. et al. Human gut microbiome aging clock based on taxonomic profiling and deep learning. iScience 23, 101199 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  80. Krištić, J. et al. Glycans are a novel biomarker of chronological and biological ages. J. Gerontology: Ser. A 69, 779–789 (2014).

    Google Scholar 

  81. Sayed, N. et al. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging. Nat. Aging 1, 598–615 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Lehallier, B. et al. Undulating changes in human plasma proteome profiles across the lifespan. Nat. Med. 25, 1843–1850 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Oh, H. S.-H. et al. Organ aging signatures in the plasma proteome track health and disease. Nature 624, 164–172 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank all members of the Dormann and Lemke laboratories for discussions, and P. Baumann and C. Niehrs for discussions on the telomere and methylation clocks. We are grateful to N. Heinss for her creative work on illustrations. D.D. and E.A.L. acknowledge funding from the CRC1551 “Polymer concepts in cellular function” of the Deutsche Forschungsgemeinschaft (project number 464588647).

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Dorothee Dormann or Edward Anton Lemke.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks the 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.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dormann, D., Lemke, E.A. Adding intrinsically disordered proteins to biological ageing clocks. Nat Cell Biol 26, 851–858 (2024). https://doi.org/10.1038/s41556-024-01423-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41556-024-01423-w

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