Reconstituted Postsynaptic Density as a Molecular Platform for Understanding Synapse Formation and Plasticity
Open accessAbstract
Synapses are semi-membraneless, protein-dense, sub-micron chemical reaction compartments responsible for signal processing in each and every neuron. Proper formation and dynamic responses to stimulations of synapses, both during development and in adult, are fundamental to functions of mammalian brains, although the molecular basis governing formation and modulation of compartmentalized synaptic assemblies is unclear. Here, we used a biochemical reconstitution approach to show that, both in solution and on supported membrane bilayers, multivalent interaction networks formed by major excitatory postsynaptic density (PSD) scaffold proteins led to formation of PSD-like assemblies via phase separation. The reconstituted PSD-like assemblies can cluster receptors, selectively concentrate enzymes, promote actin bundle formation, and expel inhibitory postsynaptic proteins. Additionally, the condensed phase PSD assemblies have features that are distinct from those in homogeneous solutions and fit for synaptic functions. Thus, we have built a molecular platform for understanding how neuronal synapses are formed and dynamically regulated.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
LLPS may be a general mechanism for assembly of PSDs, and changes in protein expression or phosphorylation can effect a desired change in synaptic strength via modulation of phase separation in the PSD.
“As we explore mechanisms for recruiting AMPARs to the synapse it will be important to consider that LLPS may be a general mechanism for assembly of PSDs and that changes in protein expression or phosphorylation can effect a desired change in synaptic strength via modulation of phase separation in the PSD (301).”
From Synaptic memory and CaMKII (2023) · cites this paper as [301]
Cites
Structural basis of long-term potentiation in single dendritic spines
Matsuzaki, M., Honkura, N., Ellis-Davies, G. C. R., & Kasai, H. (2004) · Nature · doi:10.1038/nature02617 · Cited by 2,500 · see citing works
Matsuzaki, M., Ellis-Davies, G. C. R., Nemoto, T., Miyashita, Y., Iino, M., & Kasai, H. (2001) · Nature Neuroscience · doi:10.1038/nn736 · Cited by 1,563 · cited 1× · see citing works
“Third, the volume of a spine head is proportional to the size of PSD (Harris and Stevens, 1989; Matsuzaki et al., 2001).”
A Switch Between Two-, Three-, and Four-stranded Coiled Coils in GCN4 Leucine Zipper Mutants
Harbury, P. B., Zhang, T., Kim, P. S., & Alber, T. (1993) · Science · doi:10.1126/science.8248779 · Cited by 1,490 · cited 1× · see citing works
“To partially mimic the tetrameric nature of NMDAR, we fused the last 5 residues of NR2B to the tail of a tetrameric GCN4 coiled-coil domain (GCN4NR2B, simply referred as NR2B hereafter) (Harbury et al., 1993).”
Harris, K., & Stevens, J. (1989) · The Journal of Neuroscience · doi:10.1523/jneurosci.09-08-02982.1989 · Cited by 1,073 · see citing works
Cheng, D., Hoogenraad, C. C., Rush, J., Ramm, E., Schlager, M. A., Duong, D. M., Xu, P., Wijayawardana, S. R., Hanfelt, J., Nakagawa, T., et al. (2006) · Molecular & Cellular Proteomics · doi:10.1074/mcp.d500009-mcp200 · Cited by 510 · see citing works
An Architectural Framework That May Lie at the Core of the Postsynaptic Density
Baron, M. K., Boeckers, T. M., Vaida, B., Faham, S., Gingery, M., Sawaya, M. R., Salyer, D., Gundelfinger, E. D., & Bowie, J. U. (2006) · Science · doi:10.1126/science.1118995 · Cited by 292 · see citing works
Araki, Y., Zeng, M., Zhang, M., & Huganir, R. L. (2015) · Neuron · doi:10.1016/j.neuron.2014.12.023 · Cited by 271 · see citing works
Self-citationBiochemical Computation for Spine Structural Plasticity
Nishiyama, J., & Yasuda, R. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.043 · Cited by 199 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
A 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 · see citing works
Twenty Years of SynGAP Research: From Synapses to Cognition
Gamache, T. R., Araki, Y., & Huganir, R. L. (2020) · The Journal of Neuroscience · doi:10.1523/jneurosci.0420-19.2020 · Cited by 161 · see citing works
CaMKII activation persistently segregates postsynaptic proteins via liquid phase separation
Hosokawa, T., Liu, P.-W., Cai, Q., Ferreira, J. S., Levet, F., Butler, C., Sibarita, J.-B., Choquet, D., Groc, L., Hosy, E., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00843-3 · Cited by 146 · see citing works
Self-citationNicoll, R. A., & Schulman, H. (2023) · Physiological Reviews · doi:10.1152/physrev.00034.2022 · Cited by 126 · see citing works
“It forms a homotrimer, each with a PBM that binds to the PDZ-SH3-GK tandems of PSD-95 with high avidity (301, 302).”
BackgroundSynGAP regulates synaptic plasticity and cognition independently of its catalytic activity
Araki, Y., Rajkovich, K. E., Gerber, E. E., Gamache, T. R., Johnson, R. C., Tran, T. H. N., Liu, B., Zhu, Q., Hong, I., Kirkwood, A., et al. (2024) · Science · doi:10.1126/science.adk1291 · Cited by 92 · see citing works
Ainani, H., Bouchmaa, N., Ben Mrid, R., & El Fatimy, R. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106011 · Cited by 54 · see citing works
Warnet, X. L., Bakke Krog, H., Sevillano‐Quispe, O. G., Poulsen, H., & Kjaergaard, M. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.14842 · Cited by 50 · see citing works
Bucher, M., Niebling, S., Han, Y., Molodenskiy, D., Hassani Nia, F., Kreienkamp, H.-J., Svergun, D., Kim, E., Kostyukova, A. S., Kreutz, M. R., et al. (2021) · eLife · doi:10.7554/elife.66165 · Cited by 33 · see citing works
The postsynaptic density in excitatory synapses is composed of clustered, heterogeneous nanoblocks
Sun, R., Allen, J. P., Mao, Z., Wilson, L., Haider, M., Alten, B., Zhou, Z., Wang, X., & Zhou, Q. (2025) · Journal of Cell Biology · doi:10.1083/jcb.202406133 · Cited by 20 · see citing works
- Authors
- Zeng, M., Chen, X., Guan, D., Xu, J., Wu, H., Tong, P., & Zhang, M.
- Affiliations
- Hong Kong University of Science and Technology (HK)
- Corresponding author
- Zhang, Mingjie
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2018-08
- Volume
- 174
- Issue
- 5
- Pages
- 1172-1187.e16
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2886239953
- Cited by
- 438
- References
- 8
- Citations by year
- 2026: 38 · 2025: 71 · 2024: 58 · 2023: 51 · 2022: 70 · 2021: 70 · 2020: 40 · 2019: 37 · 2018: 2 · 2014: 1
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Research Grants Council, University Grants Committee (C6004-17G, AoE-M09-12, C6004-14G, AoE/P-02/12)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Neurodevelopmental Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- postsynaptic density, synaptogenesis, synaptic plasticity, biochemical reconstitution, phase separation, multivalent protein interactions, receptor clustering, enzyme concentration
- MeSH terms
- Disks Large Homolog 4 Protein, Animals, Brain, Hippocampus, Light, Synaptic Transmission, Neuronal Plasticity, Neurons, Scattering, Radiation, Synapses, Signal Transduction, Microscopy, Confocal, Mice, Neurogenesis, Post-Synaptic Density
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review