Protein condensates as aging Maxwell fluids.


Journal

Science (New York, N.Y.)
ISSN: 1095-9203
Titre abrégé: Science
Pays: United States
ID NLM: 0404511

Informations de publication

Date de publication:
11 12 2020
Historique:
received: 05 02 2019
revised: 18 06 2019
accepted: 16 10 2020
entrez: 11 12 2020
pubmed: 12 12 2020
medline: 3 2 2021
Statut: ppublish

Résumé

Protein condensates are complex fluids that can change their material properties with time. However, an appropriate rheological description of these fluids remains missing. We characterize the time-dependent material properties of in vitro protein condensates using laser tweezer-based active and microbead-based passive rheology. For different proteins, the condensates behave at all ages as viscoelastic Maxwell fluids. Their viscosity strongly increases with age while their elastic modulus varies weakly. No significant differences in structure were seen by electron microscopy at early and late ages. We conclude that protein condensates can be soft glassy materials that we call Maxwell glasses with age-dependent material properties. We discuss possible advantages of glassy behavior for modulation of cellular biochemistry.

Identifiants

pubmed: 33303613
pii: 370/6522/1317
doi: 10.1126/science.aaw4951
doi:

Substances chimiques

Proteins 0
Solutions 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1317-1323

Subventions

Organisme : European Research Council
ID : 760067
Pays : International

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Auteurs

Louise Jawerth (L)

Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany.
Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany.

Elisabeth Fischer-Friedrich (E)

Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden, Germany.
Biotec, TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany.

Suropriya Saha (S)

Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany.

Jie Wang (J)

Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany.

Titus Franzmann (T)

Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany.
Biotec, TU Dresden, Tatzberg 47-49, 01307 Dresden, Germany.

Xiaojie Zhang (X)

EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany.

Jenny Sachweh (J)

EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany.

Martine Ruer (M)

Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany.

Mahdiye Ijavi (M)

Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany.

Shambaditya Saha (S)

Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohrgasse 3, 1030 Vienna, Austria.

Julia Mahamid (J)

EMBL Heidelberg, Meyerhofstraße 1, 69117 Heidelberg, Germany.

Anthony A Hyman (AA)

Max Planck Institute of Molecular Cell Biology and Genetics, Pfotenhauerstraße 108, 01307 Dresden, Germany. hyman@mpi-cbg.de julicher@pks.mpg.de.
Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden, Germany.
Center for Systems Biology Dresden, Pfotenhauerstr. 108, 01307 Dresden, Germany.

Frank Jülicher (F)

Max Planck Institute for the Physics of Complex Systems, Nöthnitzer Str. 38, 01187 Dresden, Germany. hyman@mpi-cbg.de julicher@pks.mpg.de.
Cluster of Excellence Physics of Life, Technische Universität Dresden, Dresden, Germany.
Center for Systems Biology Dresden, Pfotenhauerstr. 108, 01307 Dresden, Germany.

Articles similaires

Databases, Protein Protein Domains Protein Folding Proteins Deep Learning

Characterization of 3D printed composite for final dental restorations.

Lucas Eigi Borges Tanaka, Camila da Silva Rodrigues, Manassés Tércio Vieira Grangeiro et al.
1.00
Composite Resins Materials Testing Printing, Three-Dimensional Surface Properties Flexural Strength
Humans Computational Biology ROC Curve Algorithms Proteins

Strain learning in protein-based mechanical metamaterials.

Naroa Sadaba, Eva Sanchez-Rexach, Curt Waltmann et al.
1.00
Serum Albumin, Bovine Stress, Mechanical Animals Polymers Materials Testing

Classifications MeSH