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PreprintCited by 5Protein Structure and DynamicsBacterial Genetics and BiotechnologyMaterial Dynamics and Properties

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Cytoplasmic Fluidity and the Cold Life: Proteome Stability is Decoupled from Viability in Psychrophiles

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Caviglia, Beatrice, Timr, Stepan, Guiral, Marianne, Giudici-Orticoni, Marie-Thérèse, Seydel, Tilo, Beck, Christian, Peters, Judith, Sterpone, Fabio, Paciaroni, Alessandro·2025·Nature Communications

Preprint — published as 10.1038/s41467-025-65270-5

Abstract

Protein diffusion, critical for cellular metabolism, occurs in the highly crowded cytoplasm. Understanding how this dynamics changes when organisms are adapted to different thermal niches is a fundamental challenge in microbiology and biophysics. In Escherichia coli , protein diffusion undergoes a pronounced slowdown at temperatures near cellular death, coinciding with the early stages of unfolding. To determine whether this phenomenon is universal, we investigated psychrophilic and hyperthermophilic bacteria. In both species, a marked diffusion slowdown takes place at the onset of proteome melting. However, while the dynamic arrest is associated with the thermal death point for the hyperthermophilic proteome, the psychrophilic proteome maintains substantial mobility well beyond the cellular inactivation. The decoupling between metabolic viability and proteome dynamics and stability suggests that the functional processes of psychrophilic bacteria are extremely temperature sensitive. This finding echoes the behaviour of psychrophilic enzymes, manifesting a large temperature gap between optimal activity and unfolding. Protein diffusion is optimised to maintain functional fluidity at the organism’s working conditions, but its temperature dependence is controlled by the proteome folded state. Our findings redefine the relationship between cytoplasmic dynamics, proteome stability, and bacterial survival in cold environments.

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Research works printed but not linked: 81

  1. 10.3389/fmicb.2019.00780 · DOI · Paper page
  2. 10.1038/ismej.2013.8 · DOI · Paper page
  3. 10.1073/pnas.0712334105 · DOI · Paper page
  4. 10.1073/pnas.85.24.9436 · DOI
  5. 10.1007/s00253-013-5290-2 · DOI
  6. Yi, G. Y. , Kim, M. J. , Kim, H. I. , Park, J. & Baek, S. H. Hyperthermia treatment as a promising anti-cancer strategy: therapeutic targets, perspective mechanisms and synergistic combinations in experimental approaches. Antioxidants 11, (2022). · DOI
  7. 10.1007/s41745-023-00382-9 · DOI
  8. 10.1089/ast.2016.1608 · DOI
  9. 2022, Association between antibiotic resistance and increasing ambient temperature in china: an ecological study with nationwide panel data, Lancet Reg. Health West. Pac, 30, 100628
  10. 10.1021/acs.chemrev.3c00432 · DOI
  11. 10.3184/003685003783238699 · DOI
  12. 10.1099/00221287-137-10-2361 · DOI
  13. 10.1016/j.bbamem.2004.08.002 · DOI · Paper page
  14. 10.1021/bi500344j · DOI
  15. Milo, R. & Phillips, R. Cell Biology by the Numbers (Garland Science, Taylor & Francis Group, New York, 2016). · DOI · Paper page
  16. 10.1021/acscentsci.2c01078 · DOI
  17. 10.3389/fmolb.2018.00093 · DOI
  18. 10.1002/prot.21679 · DOI
  19. 10.1021/cr800373w · DOI · Paper page
  20. 10.1529/biophysj.107.124420 · DOI
  21. 10.1524/zpch.2010.6091 · DOI
  22. 10.1073/pnas.1107287108 · DOI
  23. 10.1103/PhysRev.119.863 · DOI
  24. 10.7554/eLife.82654 · DOI
  25. 10.7554/eLife.30084 · DOI
  26. 10.1039/C1SM06609A · DOI
  27. 10.1039/C4CP04944F · DOI
  28. 2008, Molecular dynamics study on nanoparticle diffusion in polymer melts: A test of the stokes–einstein law, J. Phys. Chem. C, 112, 6653, 10.1021/jp800474t · DOI
  29. 10.1038/sj.embor.7400049 · DOI
  30. 10.1021/acs.jpclett.3c03351 · DOI
  31. de Gennes, P.-G. Scaling Concepts in Polymer Physics (Cornell University Press, Ithaca, 1979).
  32. 2017, Slow-down in diffusion in crowded protein solutions correlates with transient cluster formation, J. Phys. Chem. B, 121, 11072, 10.1021/acs.jpcb.7b08785 · DOI
  33. 10.1073/pnas.1817564116 · DOI
  34. 10.1126/science.aai7825 · DOI · Paper page
  35. 10.15252/msb.20188242 · DOI
  36. 10.1021/jz1012142 · DOI
  37. 10.1099/00221287-137-10-2361 · DOI
  38. 10.1128/AEM.68.11.5379-5386.2002 · DOI
  39. 10.7717/peerj.1516 · DOI
  40. 10.1016/j.ymeth.2004.08.002 · DOI
  41. 10.1016/j.pep.2018.05.012 · DOI
  42. Nowak, M. , Olszewski, M. , Śpibida, M. & Kur, J. Characterization of single-stranded dna-binding proteins from the psychrophilic bacteria Desulfotalea psychrophila, Flavobacterium psychrophilum, Psychrobacter arcticus, Psychrobacter cryohalolentis, Psychromonas ingrahamii, Psychroflexus torquis, and Photobacterium profundum. BMC Microbiol. 14 (2014). · DOI
  43. Jung, F. , Frey, K. , Zimmer, D. & Mühlhaus, T. Deepstabp: a deep learning approach for the prediction of thermal protein stability. Int. J. Mol. Sci. 24 (2023). · DOI
  44. 10.1046/j.1365-2672.1998.00519.x · DOI
  45. 10.1128/JB.01377-08 · DOI
  46. 10.1016/j.bpj.2010.10.036 · DOI
  47. 10.1073/pnas.1114477108 · DOI · Paper page
  48. 10.1038/nmeth.4067 · DOI
  49. 10.1073/pnas.1800690115 · DOI
  50. 10.1016/j.bpj.2016.07.024 · DOI
  51. 10.1073/pnas.2122957119 · DOI
  52. 10.1016/j.sbi.2023.102625 · DOI
  53. 2025, Single-molecule diffusivity quantification in Xenopus egg extracts elucidates physicochemical properties of the cytoplasm, Proc. Natl. Acad. Sci, 121, e2411402121
  54. 10.1021/jz3019379 · DOI
  55. 10.1007/s11157-017-9443-0 · DOI · Paper page
  56. 10.1016/j.bpj.2009.11.048 · DOI
  57. 10.1038/sj.embor.7400662 · DOI · Paper page
  58. Nowak, J. S. & Otzen, D. E. Helping proteins come in from the cold: 5 burning questions about cold-active enzymes. BBA Adv. 100104 (2024). · DOI
  59. 10.1016/j.biochi.2012.05.013 · DOI
  60. Gault, S. , Higgins, P. , Cockell, C. & Gillies, K. A meta-analysis of the activity, stability, and mutational characteristics of temperature-adapted enzymes. Biosci. Rep. 41 (2021). · DOI
  61. 10.1016/j.semcdb.2017.09.003 · DOI
  62. 2018, How to calculate thermostability of enzymes using a simple approach, Biochem. Mol. Biol. Educ, 46, 398, 10.1002/bmb.21127 · DOI
  63. 10.1016/j.tibs.2010.05.001 · DOI
  64. 10.1038/s41467-020-16341-2 · DOI
  65. 10.1002/chem.202001973 · DOI
  66. 10.1128/jb.178.11.2999-3007.1996 · DOI
  67. 10.3389/fmicb.2022.841359 · DOI
  68. 10.1038/srep12711 · DOI
  69. 10.1074/jbc.M508034200 · DOI
  70. 10.1002/jcc.10216 · DOI · Paper page
  71. 10.1002/jcc.21224 · DOI · Paper page
  72. 10.1063/1.445869 · DOI · Paper page
  73. 10.1063/1.2408420 · DOI · Paper page
  74. 10.1063/1.448118 · DOI · Paper page
  75. 10.1063/1.328693 · DOI · Paper page
  76. 10.1063/1.464397 · DOI · Paper page
  77. Hess, B. , Bekker, H. , Berendsen, H. & Fraaije, J. Lincs: a linear constraint solver for molecular simulations. J. Comput. Chem. 18, (1998). · DOI
  78. Miyamoto, S. & Kollman, P. Settle: an analytical version of the shake and rattle algorithm for rigid water models. J. Comput. Chem. 13, (1992). · DOI
  79. Yeh, I.-C. & Hummer, G. System-size dependence of diffusion coefficients and viscosities from molecular dynamics simulations with periodic boundary conditions. J. Phys. Chem. B 108 (2004). · DOI · Paper page
  80. 10.1021/acs.jpclett.8b01090 · DOI
  81. Cisse, A. , Peters, J. , Lazzara, G. & Chiappisi, L. PyDSC: a simple tool to treat differential scanning calorimetry data. J. Therm. Anal. Calorim. 145 (2020). · DOI

Metadata

Authors
Caviglia, B., Timr, S., Guiral, M., Giudici-Orticoni, M.-T., Seydel, T., Beck, C., Peters, J., Sterpone, F., & Paciaroni, A.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • J. Heyrovský Institute of Physical Chemistry, Czech Academy of Sciences,182 00 Prague, Czechia
  • Laboratoire de Bioénergétique et Ingénierie des Protéines, BIP, CNRS, Aix-Marseille Université, 13400 Marseille, France
  • Institut Laue-Langevin (FR)
  • University of Perugia (IT)
Corresponding author
  • Peters, Judith
  • Sterpone, Fabio
  • Paciaroni, Alessandro
Venue
Nature Communications
Publisher
openRxiv
Published
2025-06-27
Volume
16
Issue
1
Pages
10345-10345
ISSN
2041-1723 (ISSN-L)
OpenAlex
W4416576149
Cited by
5
References
1
Citations by year
2026: 5
FWCI
1.50
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by-nc-nd)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • European Commission (CUP B43C22000470005, CUP J97G22000170005, ECS00000041)
  • Agence Nationale de la Recherche (ANR-22-CE95-0002, LABX-0011-01, ANR-11-EQPX-0008, ANR-11-LABX-0011)
  • Akademie Věd České Republiky (LQ200402301)
  • Centre National de la Recherche Scientifique (ANR-11-LABX-0011-01, ANR-11-LABX-0011, 11-LABX-0011-01)
  • Grand Équipement National De Calcul Intensif
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Bacterial Genetics and Biotechnology
  • Physical Sciences › Materials Science › Materials Chemistry › Material Dynamics and Properties
Keywords
psychrophiles, hyperthermophiles, protein diffusion, thermal death point, protein unfolding, cytoplasmic crowding, Escherichia coli, bacterial viability, cold adaptation, temperature dependence of diffusion
MeSH terms
Cold Temperature, Cytoplasm, Diffusion, Escherichia coli, Proteome, Escherichia coli Proteins, Microbial Viability, Protein Stability

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