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The filamentous ultrastructure of the PopZ condensate is required for its cellular function
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Abstract
Abstract Biomolecular condensates play key roles in the spatiotemporal regulation of cellular processes. Yet, the relationship between atomic features and condensate function remains poorly understood. We studied this relationship using the polar organizing protein Z (PopZ) as a model system, revealing how its material properties and cellular function depend on its ultrastructure. We revealed PopZ’s hierarchical assembly into a filamentous condensate by integrating cryo-electron tomography, biochemistry, single-molecule techniques, and molecular dynamics simulations. The helical domain drives filamentation and condensation, while the disordered domain inhibits them. Phase-dependent conformational changes prevent interfilament contacts in the dilute phase and expose client binding sites in the dense phase. These findings establish a multiscale framework that links molecular interactions and condensate ultrastructure to macroscopic material properties that drive cellular function.
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Highly accurate protein structure prediction with AlphaFold
Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03819-2 · Cited by 43,764
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Self-citationA framework for understanding the functions of biomolecular condensates across scales
Lyon, A. S., Peeples, W. B., & Rosen, M. K. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00303-z · Cited by 895
Flagged first, then by citations
Research works printed but not linked: 87
- Banani, S. F., Lee, H. O., Hyman, A. A. & Rosen, M. K. Biomolecular condensates: organizers of cellular biochemistry. Nat. Rev. Mol. Cell Biol. 18, 285–298 (2017). · DOI
- Shin, Y. & Brangwynne, C. P. Liquid phase condensation in cell physiology and disease. Science 357, eaaf4382 (2017). · DOI
- Boeynaems, S. et al. Phase separation in biology and disease; current perspectives and open questions. J. Mol. Biol. 435, 167971 (2023). · DOI
- Choi, J. M., Holehouse, A. S. & Pappu, R. V. Physical principles underlying the complex biology of intracellular phase transitions. Annu. Rev. Biophys. 49, 107–133 (2020). · DOI
- Pei, G., Lyons, H., Li, P. & Sabari, B. R. Transcription regulation by biomolecular condensates. Nat. Rev. Mol. Cell Biol. 26, 213–236 (2025). · DOI
- Su, X. et al. Phase separation of signaling molecules promotes T cell receptor signal transduction. Science 352, 595–599 (2016). · DOI
- 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). · DOI
- Visser, B. S., Lipinski, W. P. & Spruijt, E. The role of biomolecular condensates in protein aggregation. Nat. Rev. Chem. 8, 686–700 (2024). · DOI
- Pappu, R. V., Cohen, S. R., Dar, F., Farag, M. & Kar, M. Phase transitions of associative biomacromolecules. Chem. Rev. 123, 8945–8987 (2023). · DOI
- Mittag, T. & Pappu, R. V. A conceptual framework for understanding phase separation and addressing open questions and challenges. Mol. Cell 82, 2201–2214 (2022). · DOI
- Gouveia, B. et al. Capillary forces generated by biomolecular condensates. Nature 609, 255–264 (2022). · DOI
- Alshareedah, I. et al. Sequence-specific interactions determine viscoelasticity and ageing dynamics of protein condensates. Nat. Phys. 20, 1482–1491 (2024). · DOI
- Feric, M. et al. Coexisting liquid phases underlie nucleolar subcompartments. Cell 165, 1686–1697 (2016). · DOI
- Posey, A. E. et al. Biomolecular condensates are characterized by interphase electric potentials. J. Am. Chem. Soc. 146, 28268–28281 (2024). · DOI
- Peran, I. & Mittag, T. Molecular structure in biomolecular condensates. Curr. Opin. Struct. Biol. 60, 17–26 (2020). · DOI
- Bienz, M. Head-to-tail polymerization in the assembly of biomolecular condensates. Cell 182, 799–811 (2020). · DOI
- Fletcher, D. A. & Mullins, R. D. Cell mechanics and the cytoskeleton. Nature 463, 485–492 (2010). · DOI
- Berkamp, S., Mostafavi, S. & Sachse, C. Structure and function of p62/SQSTM1 in the emerging framework of phase separation. FEBS J. 288, 6927–6941 (2021). · DOI
- Bouchard, J. J. et al. Cancer mutations of the tumor suppressor SPOP disrupt the formation of active, phase-separated compartments. Mol Cell 72, 19–36 e8 (2018). · DOI
- Weirich, K. L. et al. Liquid behavior of cross-linked actin bundles. Proc. Natl Acad. Sci. USA 114, 2131–2136 (2017). · DOI
- Bowman, G. R. et al. A polymeric protein anchors the chromosomal origin/ParB complex at a bacterial cell pole. Cell 134, 945–955 (2008). · DOI
- Ebersbach, G., Briegel, A., Jensen, G. J. & Jacobs-Wagner, C. A self-associating protein critical for chromosome attachment, division, and polar organization in Caulobacter. Cell 134, 956–968 (2008). · DOI
- Bowman, G. R. et al. Caulobacter PopZ forms a polar subdomain dictating sequential changes in pole composition and function. Mol. Microbiol. 76, 173–189 (2010). · DOI
- Ettema, T. J. & Andersson, S. G. The α-proteobacteria: the Darwin finches of the bacterial world. Biol. Lett. 5, 429–432 (2009). · DOI
- Tsokos, C. G. & Laub, M. T. Polarity and cell fate asymmetry in Caulobacter crescentus. Curr. Opin. Microbiol. 15, 744–750 (2012). · DOI
- Govers, S. K. & Jacobs-Wagner, C. Caulobacter crescentus: model system extraordinaire. Curr. Biol. 30, R1151–R1158 (2020). · DOI
- Lasker, K., Mann, T. H. & Shapiro, L. An intracellular compass spatially coordinates cell cycle modules in Caulobacter crescentus. Curr. Opin. Microbiol. 33, 131–139 (2016). · DOI
- Lasker, K. et al. Selective sequestration of signalling proteins in a membraneless organelle reinforces the spatial regulation of asymmetry in Caulobacter crescentus. Nat. Microbiol. 5, 418–429 (2020). · DOI
- Lasker, K. et al. The material properties of a bacterial-derived biomolecular condensate tune biological function in natural and synthetic systems. Nat. Commun. 13, 5643 (2022). · DOI
- Heebner, J. E. et al. Deep learning-based segmentation of cryo-electron tomograms. J. Vis. Exp. (189), e64435 (2022). · DOI
- Oosawa, F. & Kasai, M. A theory of linear and helical aggregations of macromolecules. J. Mol. Biol. 4, 10–21 (1962). · DOI
- Romberg, L., Simon, M. & Erickson, H. P. Polymerization of Ftsz, a bacterial homolog of tubulin. Is assembly cooperative? J. Biol. Chem. 276, 11743–11753 (2001). · DOI
- Toro-Nahuelpan, M., Plitzko, J. M., Schüler, D. & Pfeiffer, D. In vivo architecture of the polar organizing protein Z (PopZ) meshwork in the alphaproteobacteria Magnetospirillum gryphiswaldense and Caulobacter crescentus. J. Mol. Biol. 434, 167423 (2022). · DOI
- Bowman, G. R. et al. Oligomerization and higher-order assembly contribute to sub-cellular localization of a bacterial scaffold. Mol. Microbiol. 90, 776–795 (2013). · DOI
- Laloux, G. & Jacobs-Wagner, C. Spatiotemporal control of PopZ localization through cell cycle-coupled multimerization. J. Cell Biol. 201, 827–841 (2013). · DOI
- Holmes, J. A. et al. Caulobacter PopZ forms an intrinsically disordered hub in organizing bacterial cell poles. Proc. Natl Acad. Sci. USA 113, 12490–12495 (2016). · DOI
- Ptacin, J. L. et al. Bacterial scaffold directs pole-specific centromere segregation. Proc. Natl Acad. Sci. USA 111, E2046–E2055 (2014). · DOI
- Marzahn, M. R. et al. Higher-order oligomerization promotes localization of SPOP to liquid nuclear speckles. EMBO J. 35, 1254–1275 (2016). · DOI
- Soltermann, F. et al. Quantifying protein–protein interactions by molecular counting with mass photometry. Angew. Chem. Int. Ed. Engl. 59, 10774–10779 (2020). · DOI
- Young, G. et al. Quantitative mass imaging of single biological macromolecules. Science 360, 423–427 (2018). · DOI
- Howlett, G. J., Minton, A. P. & Rivas, G. Analytical ultracentrifugation for the study of protein association and assembly. Curr. Opin. Chem. Biol. 10, 430–436 (2006). · DOI
- Agudo-Canalejo, J. et al. Wetting regulates autophagy of phase-separated compartments and the cytosol. Nature 591, 142–146 (2021). · DOI
- Alshareedah, I., Kaur, T. & Banerjee, P. R. Methods for characterizing the material properties of biomolecular condensates. Methods Enzymol. 646, 143–183 (2021). · DOI
- Ditlev, J. A., Case, L. B. & Rosen, M. K. Who’s in and who’s out—compositional control of biomolecular condensates. J. Mol. Biol. 430, 4666–4684 (2018). · DOI
- Nordyke, C. T., Ahmed, Y., Puterbaugh, R. Z., Bowman, G. R. & Varga, K. Intrinsically disordered bacterial polar organizing protein Z, PopZ, interacts with protein binding partners through an N-terminal molecular recognition feature. J. Mol. Biol. 432, 6092–6107 (2020). · DOI
- Biondi, E. G. et al. Regulation of the bacterial cell cycle by an integrated genetic circuit. Nature 444, 899–904 (2006). · DOI
- Scholl, D. & Deniz, A. A. Conformational freedom and topological confinement of proteins in biomolecular condensates. J. Mol. Biol. 434, 167348 (2022). · DOI
- Saar, K. L. et al. Theoretical and data-driven approaches for biomolecular condensates. Chem. Rev. 123, 8988–9009 (2023). · DOI
- Latham, A. P. & Zhang, B. Unifying coarse-grained force fields for folded and disordered proteins. Curr. Opin. Struct. Biol. 72, 63–70 (2022). · DOI
- Bentley, E. P., Scholl, D., Wright, P. E. & Deniz, A. A. Coupling of binding and differential subdomain folding of the intrinsically disordered transcription factor CREB. FEBS Lett. 597, 917–932 (2023). · DOI
- Lerner, E. et al. FRET-based dynamic structural biology: challenges, perspectives and an appeal for open-science practices. eLife 10, e60416 (2021). · DOI
- Fitzkee, N. C. & Rose, G. D. Reassessing random-coil statistics in unfolded proteins. Proc. Natl Acad. Sci. USA 101, 12497–12502 (2004). · DOI
- Lotthammer, J. M., Ginell, G. M., Griffith, D., Emenecker, R. J. & Holehouse, A. S. Direct prediction of intrinsically disordered protein conformational properties from sequence. Nat. Methods 21, 465–476 (2024). · DOI
- Das, R. K., Ruff, K. M. & Pappu, R. V. Relating sequence encoded information to form and function of intrinsically disordered proteins. Curr. Opin. Struct. Biol. 32, 102–112 (2015). · DOI
- Antonik, M., Felekyan, S., Gaiduk, A. & Seidel, C. A. Separating structural heterogeneities from stochastic variations in fluorescence resonance energy transfer distributions via photon distribution analysis. J. Phys. Chem. B 110, 6970–6978 (2006). · DOI
- Livny, J., Yamaichi, Y. & Waldor, M. K. Distribution of centromere-like parS sites in bacteria: insights from comparative genomics. J. Bacteriol. 189, 8693–8703 (2007). · DOI
- Ptacin, J. L. et al. A spindle-like apparatus guides bacterial chromosome segregation. Nat. Cell Biol. 12, 791–798 (2010). · DOI
- Shebelut, C. W., Guberman, J. M., van Teeffelen, S., Yakhnina, A. A. & Gitai, Z. Caulobacter chromosome segregation is an ordered multistep process. Proc. Natl Acad. Sci. USA 107, 14194–14198 (2010). · DOI
- Puentes-Rodriguez, S. G., Norcross, J. D. & Mera, P. E. To let go or not to let go: how ParA can impact the release of the chromosomal anchoring in Caulobacter crescentus. Nucleic Acids Res. 51, 12275–12287 (2023). · DOI
- Tsai, J. W. & Alley, M. R. Proteolysis of the Caulobacter McpA chemoreceptor is cell cycle regulated by a ClpX-dependent pathway. J. Bacteriol. 183, 5001–5007 (2001). · DOI
- Mastronarde, D. N. Automated electron microscope tomography using robust prediction of specimen movements. J. Struct. Biol. 152, 36–51 (2005). · DOI
- Eisenstein, F. et al. Parallel cryo electron tomography on in situ lamellae. Nat. Methods 20, 131–138 (2023). · DOI
- Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017). · DOI
- Buchholz, T. O. et al. Content-aware image restoration for electron microscopy. Methods Cell. Biol. 152, 277–289 (2019). · DOI
- Liu, Y. T. et al. Isotropic reconstruction for electron tomography with deep learning. Nat. Commun. 13, 6482 (2022).
- Chen, M. et al. A complete data processing workflow for cryo-ET and subtomogram averaging. Nat. Methods 16, 1161–1168 (2019). · DOI
- Winkler, H. 3D reconstruction and processing of volumetric data in cryo-electron tomography. J. Struct. Biol. 157, 126–137 (2007). · DOI
- Zhang, K. Gctf: real-time CTF determination and correction determination and correction. J. Struct. Biol. 193, 1–12 (2016). · DOI
- Morado, D. R., Hu, B. & Liu, J. Using Tomoauto: a protocol for high-throughput automated cryo-electron tomography. J. Vis. Exp. (107), e53608 (2016). · DOI
- Punjani, A., Rubinstein, J. L., Fleet, D. J. & Brubaker, M. A. cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination. Nat. Methods 14, 290–296 (2017). · DOI · Paper page
- Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015). · DOI
- Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012). · DOI · Paper page
- Ducret, A., Quardokus, E. M. & Brun, Y. V. MicrobeJ, a tool for high throughput bacterial cell detection and quantitative analysis. Nat. Microbiol. 1, 16077 (2016). · DOI
- Schuck, P. Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling. Biophys. J. 78, 1606–1619 (2000). · DOI
- Philo, J. S. SEDNTERP: a calculation and database utility to aid interpretation of analytical ultracentrifugation and light scattering data. Eur. Biophys. J. 52, 233–266 (2023). · DOI
- Clementi, C., Nymeyer, H. & Onuchic, J. N. Topological and energetic factors: what determines the structural details of the transition state ensemble and ‘en-route’ intermediates for protein folding? An investigation for small globular proteins. J. Mol. Biol. 298, 937–953 (2000). · DOI
- Latham, A. P. & Zhang, B. Consistent force field captures homologue-resolved HP1 phase separation. J. Chem. Theory Comput. 17, 3134–3144 (2021). · DOI
- Regy, R. M., Thompson, J., Kim, Y. C. & Mittal, J. Improved coarse-grained model for studying sequence dependent phase separation of disordered proteins. Protein Sci. 30, 1371–1379 (2021). · DOI
- Liu, S., Wang, C., Latham, A. P., Ding, X. & Zhang, B. OpenABC enables flexible, simplified, and efficient GPU accelerated simulations of biomolecular condensates. PLoS Comput. Biol. 19, e1011442 (2023).
- Dignon, G. L., Zheng, W., Best, R. B., Kim, Y. C. & Mittal, J. Relation between single-molecule properties and phase behavior of intrinsically disordered proteins. Proc. Natl Acad. Sci. USA 115, 9929–9934 (2018). · DOI
- Michaud-Agrawal, N., Denning, E. J., Woolf, T. B. & Beckstein, O. MDAnalysis: a toolkit for the analysis of molecular dynamics simulations. J. Comput. Chem. 32, 2319–2327 (2011). · DOI
- Gowers, R. J. et al. MDAnalysis: a Python package for the rapid analysis of molecular dynamics simulations. In Proceedings of the 15th Python in Science Conference (eds Benthall, S. & Rostrup, S.) (SciPy, 2016). · DOI
- Dignon, G. L., Zheng, W., Kim, Y. C., Best, R. B. & Mittal, J. Sequence determinants of protein phase behavior from a coarse-grained model. PLoS Comput. Biol. 14, e1005941 (2018). · DOI
- Schrimpf, W., Barth, A., Hendrix, J. & Lamb, D. C. PAM: a framework for integrated analysis of imaging, single-molecule, and ensemble fluorescence data. Biophys. J. 114, 1518–1528 (2018). · DOI
- Hellenkamp, B. et al. Precision and accuracy of single-molecule FRET measurements—a multi-laboratory benchmark study. Nat. Methods 15, 669–676 (2018). · DOI · Paper page
- Kudryavtsev, V. et al. Combining MFD and PIE for accurate single-pair Förster resonance energy transfer measurements. ChemPhysChem 13, 1060–1078 (2012). · DOI
- Tomov, T. E. et al. Disentangling subpopulations in single-molecule FRET and ALEX experiments with photon distribution analysis. Biophys. J. 102, 1163–1173 (2012). · DOI
Metadata
- Authors
- Scholl, D., Boyd, T., Latham, A. P., Salazar, A., Khan, A. M. A. M., Boeynaems, S., Holehouse, A. S., Lander, G. C., Sali, A., Park, D., Deniz, A. A., & Lasker, K.
- Affiliations
- Scripps Research Institute (US)
- University of California, San Francisco (US)
- Baylor College of Medicine (US)
- Washington University in St. Louis (US)
- Corresponding author
- Park, Donghyun
- Deniz, Ashok A.
- Lasker, Keren
- ORCID
- Venue
- Nature Structural & Molecular Biology
- Published
- 2026-02-02
- Volume
- 33
- Issue
- 3
- Pages
- 420-432
- ISSN
- 1545-9985 (ISSN-L)
- 1545-9993
- PMC
- PMC11703246
- OpenAlex
- W7127082149
- Cited by
- 14
- References
- 5
- Citations by year
- 2026: 12
- FWCI
- 24.80
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Structural & Molecular Biology (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Digital Commons-TMC (Texas Medical Center) (submittedVersion)
- Funders
- National Institutes of Health (1s10od032467-01)
- National Institute of General Medical Sciences (R01GM083960, F32GM150243, R35GM130375)
- National Institute of Neurological Disorders and Stroke (DP2NS142714, R01NS095892)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Microtubule and mitosis dynamics
- Keywords
- PopZ, biomolecular condensates, helical domain, intrinsically disordered regions, phase separation, cell growth
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