journal article·2026-01Open access

Nanoscopic Mapping of the Extracellular Space in Amyloid Plaque‐rich Cortex

Juan Estaún‐Panzano, Yulia Dembitskaya, Ivo Calaresu, Somen Nandi, Quentin Gresil, Evelyne Doudnikoff, Thierry Leste‐Lasserre, Thierry Amédée, Laurent Cognet, Laurent Groc, Urs Valentin Nägerl, Erwan Bezard

Advanced Science· Volume 13· Issue 1

Abstract

Abstract A hallmark of Alzheimer's disease (AD) is the accumulation of amyloid plaques, primarily composed of misfolded amyloid β (Aβ) peptides. Complementary high‐resolution imaging techniques are employed to investigate the plaque penetrability and the extracellular space (ECS) rheology in a mouse model of AD. Two‐photon shadow imaging in vivo confirms that a dense ring of cells surrounds cortical amyloid plaques but highlights the diffusional penetrability of the amyloid core. Quantum dot tracking unveils that ECS diffusional parameters are heterogeneous in and around plaques, with an elevated diffusivity within and around plaques compared to wild‐type‐tissue. The amyloid core shows low nanoparticle density, varying by plaque phenotype. Carbon nanotube tracking confirms these altered local rheological properties at the level of the whole cortex of AD mice. Finally, the extracellular matrix is found to be dysregulated within the amyloid plaque, which may account for the observed alterations in diffusivity. This study provides fresh insights for understanding Aβ plaque penetration, a prerequisite for therapeutic development.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Alzheimer's disease research and treatments · Neuroinflammation and Neurodegeneration Mechanisms · Barrier Structure and Function Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institut des Maladies Neurodégénératives CNRS Université de Bordeaux UMR 5293 Bordeaux F‐33000 France

Institut Interdisciplinaire de Neurosciences CNRS Université de Bordeaux UMR 5297 Bordeaux F‐33000 France

Laboratoire Photonique Numérique et Nanosciences CNRS Université de Bordeaux UMR 5298 Talence F‐33400 France

Laboratoire Photonique Numérique et Nanosciences IOGS CNRS UMR 5298 Talence F‐33400 France

Neurocentre Magendie INSERM Université de Bordeaux U1215 Bordeaux 33000 France

Institut für Anatomie und Zellbiologie Universitätsmedizin Göttingen Georg‐August‐Universität 37075 Göttingen Germany

Funding

Human Frontier Science Program · H2020 European Research Council

References (89)

Show source-provided references
1. 10.1038/s41582-024-00940-410.1038/s41582-024-00940-4 ↗
2. 10.1007/s13311-021-01146-y10.1007/s13311-021-01146-y ↗
3. 10.1126/sageke.2006.6.re110.1126/sageke.2006.6.re1 ↗
4. 10.1016/j.arr.2021.10133910.1016/j.arr.2021.101339 ↗
5. 10.1038/s41572-021-00269-y10.1038/s41572-021-00269-y ↗
6. 10.1016/j.bpj.2017.06.05210.1016/j.bpj.2017.06.052 ↗
7. 10.3389/fncel.2022.84421110.3389/fncel.2022.844211 ↗
8. 10.1038/s41467-020-17328-910.1038/s41467-020-17328-9 ↗
9. 10.1038/nrn355010.1038/nrn3550 ↗
10. 10.1016/j.nbd.2021.10534510.1016/j.nbd.2021.105345 ↗
11. 10.1038/s41467-023-42055-210.1038/s41467-023-42055-2 ↗
12. 10.1111/bpa.1289710.1111/bpa.12897 ↗
13. 10.1038/s41593-018-0329-410.1038/s41593-018-0329-4 ↗
14. 10.1186/s13024-021-00465-010.1186/s13024-021-00465-0 ↗
15. 10.1016/j.neuron.2016.05.00310.1016/j.neuron.2016.05.003 ↗
16. 10.1038/s41598-020-68045-810.1038/s41598-020-68045-8 ↗
17. 10.1016/j.celrep.2023.11247810.1016/j.celrep.2023.112478 ↗
18. 10.1038/tp.2017.13410.1038/tp.2017.134 ↗
19. 10.1186/1479-5876-10-510.1186/1479-5876-10-5 ↗
20. 10.1007/s12264-019-00393-610.1007/s12264-019-00393-6 ↗
21. 10.3109/1052029090338944510.3109/10520290903389445 ↗
22. 10.1016/j.jneuroim.2024.57834210.1016/j.jneuroim.2024.578342 ↗
23. 10.1038/ncomms717610.1038/ncomms7176 ↗
24. 10.1007/s00401-024-02775-110.1007/s00401-024-02775-1 ↗
25. 10.1016/j.cbpa.2014.04.01510.1016/j.cbpa.2014.04.015 ↗
26. 10.1126/science.115208910.1126/science.1152089 ↗
27. 10.3390/ijms23201240110.3390/ijms232012401 ↗
28. 10.1007/s00401-018-1812-410.1007/s00401-018-1812-4 ↗
29. 10.1016/j.nbd.2022.10598110.1016/j.nbd.2022.105981 ↗
30. 10.1152/physrev.00027.200710.1152/physrev.00027.2007 ↗
31. 10.3390/ijms2408704910.3390/ijms24087049 ↗
32. 10.1038/s41598-023-33677-z10.1038/s41598-023-33677-z ↗
33. 10.1523/JNEUROSCI.2637-09.200910.1523/JNEUROSCI.2637-09.2009 ↗
34. 10.1006/meth.2001.120110.1006/meth.2001.1201 ↗
35. 10.1038/s41551-022-00912-310.1038/s41551-022-00912-3 ↗
36. 10.1038/s41590-021-00913-510.1038/s41590-021-00913-5 ↗
37. 10.1016/j.ebiom.2020.10291910.1016/j.ebiom.2020.102919 ↗
38. 10.3389/fnint.2022.89640010.3389/fnint.2022.896400 ↗
39. 10.1155/2014/90863610.1155/2014/908636 ↗
40. 10.1177/0271678X1665555110.1177/0271678X16655551 ↗
41. 10.1101/cshperspect.a00505810.1101/cshperspect.a005058 ↗
42. 10.1038/s41423-021-00751-310.1038/s41423-021-00751-3 ↗
43. 10.1016/j.ymeth.2019.03.00510.1016/j.ymeth.2019.03.005 ↗
44. 10.1021/acsnano.5c0217110.1021/acsnano.5c02171 ↗
45. 10.1038/nnano.2016.24810.1038/nnano.2016.248 ↗
46. 10.1016/j.cell.2018.02.00710.1016/j.cell.2018.02.007 ↗
47. 10.1038/s41531-024-00850-810.1038/s41531-024-00850-8 ↗
48. 10.1021/mp300495e10.1021/mp300495e ↗
49. 10.1371/journal.pone.013392110.1371/journal.pone.0133921 ↗
50. Odackal J. · J. Visualized Exp. · 2017 · 125
51. 10.3389/fnins.2020.57075010.3389/fnins.2020.570750 ↗
52. 10.1117/1.NPh.9.3.03221010.1117/1.NPh.9.3.032210 ↗
53. 10.1074/jbc.M40367220010.1074/jbc.M403672200 ↗
54. 10.1016/j.neuron.2019.12.01510.1016/j.neuron.2019.12.015 ↗
55. 10.1126/scitranslmed.adk999310.1126/scitranslmed.adk9993 ↗
56. 10.1124/molpharm.123.00072610.1124/molpharm.123.000726 ↗
57. 10.1126/scitranslmed.300374810.1126/scitranslmed.3003748 ↗
58. 10.1002/adma.20231145710.1002/adma.202311457 ↗
59. 10.1016/j.nbd.2020.10495610.1016/j.nbd.2020.104956 ↗
60. 10.1016/j.neuropharm.2014.07.01510.1016/j.neuropharm.2014.07.015 ↗
61. 10.3389/fnagi.2020.0026510.3389/fnagi.2020.00265 ↗
62. 10.1074/jbc.M113.51544510.1074/jbc.M113.515445 ↗
63. 10.1186/s40478-017-0467-z10.1186/s40478-017-0467-z ↗
64. 10.1101/cshperspect.a00633810.1101/cshperspect.a006338 ↗
65. 10.1096/fj.13-22966610.1096/fj.13-229666 ↗
66. 10.1126/science.124122410.1126/science.1241224 ↗
67. 10.1146/annurev-immunol-101921-03522210.1146/annurev-immunol-101921-035222 ↗
68. 10.3389/fnins.2022.80747310.3389/fnins.2022.807473 ↗
69. 10.1016/j.pharmthera.2013.12.00910.1016/j.pharmthera.2013.12.009 ↗
70. 10.1007/s00401-006-0041-410.1007/s00401-006-0041-4 ↗
71. 10.1016/j.neurobiolaging.2005.04.01110.1016/j.neurobiolaging.2005.04.011 ↗
72. 10.1093/jnen/63.5.41810.1093/jnen/63.5.418 ↗
73. 10.1016/j.bbr.2012.12.05510.1016/j.bbr.2012.12.055 ↗
74. 10.1016/j.bbr.2006.11.04410.1016/j.bbr.2006.11.044 ↗
75. 10.1016/j.jbc.2021.10100410.1016/j.jbc.2021.101004 ↗
76. 10.1016/S0969-9961(03)00084-610.1016/S0969-9961(03)00084-6 ↗
77. 10.1016/j.ajpath.2012.08.01210.1016/j.ajpath.2012.08.012 ↗
78. 10.1007/s00401-024-02775-110.1007/s00401-024-02775-1 ↗
79. 10.1073/pnas.220926012010.1073/pnas.2209260120 ↗
80. 10.3390/cancers1101000510.3390/cancers11010005 ↗
81. 10.1021/acsnano.8b0390010.1021/acsnano.8b03900 ↗
82. 10.3171/2019.6.JNS19153110.3171/2019.6.JNS191531 ↗
83. 10.1093/hmg/ddh01910.1093/hmg/ddh019 ↗
84. 10.1038/ncomms402410.1038/ncomms4024 ↗
85. 10.1093/bioinformatics/btu20210.1093/bioinformatics/btu202 ↗
86. 10.1038/nbt.362510.1038/nbt.3625 ↗
87. 10.1373/clinchem.2008.11279710.1373/clinchem.2008.112797 ↗
88. 10.1007/s11103-012-9885-210.1007/s11103-012-9885-2 ↗
89. 10.1006/meth.2001.126210.1006/meth.2001.1262 ↗