Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells
Source abstract
Abstract
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale scaffold consisting of a honeycomb microframe covered on both sides with a monolayer of cross-linked gelatin nanofibers. Cortical neural precursor cells were first produced from human-induced pluripotent stem cells and then loaded into the scaffold for a long period of differentiation toward cortical neural cells. As a result, neurons and astrocytes self-organized in the scaffold to form clusters in each of the honeycomb compartments with remarkable inter-cluster connections. These cells highly expressed neuron- and astrocyte-specific proteins, including NF200, tau, synapsin I, and glial fibrillary acidic protein, and showed spatially correlated neural activities. Two types of neural clusters, that is, spheroid-like and hourglass-like clusters, were found, indicating the complexity of neural-scaffold interaction and the variability of three-dimensional neural organization. Furthermore, we incorporated a reconstituted basement membrane into the scaffold and performed co-culture of the neural network with brain microvascular endothelial cells. As a proof of concept, an improved neurovascular unit model was tested, showing large astrocytic end-feet on the back side of the endothelium.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Tissue Engineering and Regenerative Medicine · 3D Printing in Biomedical Research · Neuroscience and Neural Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
PASTEUR, Département de Chimie, École Normale Supérieure, PSL Université, Sorbonne Université, CNRS, 75005 Paris, France
MesoBioTech, 231 Rue Saint-Honoré, 75001 Paris, France
Funding
Agence Nationale de la Recherche · Institut Pierre-Gilles de Gennes · R??gion Ile-de-France · Carnot IPGG · European Commission Cost Action project BIONECA · PSL-valorization
References (67)
Show source-provided references
1. 10.1016/j.cell.2011.06.03010.1016/j.cell.2011.06.030 ↗
2. Shapson-Coe, A.; Januszewski, M.; Berger, D. R.; Pope, A.; Wu, Y.; Blakely, T.; Schalek, R. L.; Li, P. H.; Wang, S.; Maitin-Shepard, J.; Karlupia, N.; Dorkenwald, S.; Sjostedt, E.; Leavitt, L.; Lee, D.; Bailey, L.; Fitzmaurice, A.; Kar, R.; Field, B.; Wu, H.; Wagner-Carena, J.; Aley, D.; Lau, J.; Lin, Z.; Wei, D.; Pfister, H.; Peleg, A.; Jain, V.; Lichtman, J. W. A connectomic study of a petascale fragment of human cerebral cortex. 2021, bioRxiv:2021.05.29.446289.10.1101/2021.05.29.446289 ↗
3. 10.15252/embj.20169581010.15252/embj.201695810 ↗
4. 10.1074/jbc.r116.76021510.1074/jbc.r116.760215 ↗
5. 10.1038/nrd.2015.2110.1038/nrd.2015.21 ↗
6. 10.3389/fnins.2020.0033410.3389/fnins.2020.00334 ↗
7. 10.3390/ijms1809196510.3390/ijms18091965 ↗
8. 10.1038/srep0548910.1038/srep05489 ↗
9. 10.1038/srep2964010.1038/srep29640 ↗
10. 10.1016/j.copbio.2020.06.00910.1016/j.copbio.2020.06.009 ↗
11. 10.1186/s12987-020-00183-710.1186/s12987-020-00183-7 ↗
12. 10.1093/brain/awaa26810.1093/brain/awaa268 ↗
13. 10.1021/acsami.0c1661610.1021/acsami.0c16616 ↗
14. 10.1038/s41467-019-13896-710.1038/s41467-019-13896-7 ↗
15. 10.1002/adhm.20190148610.1002/adhm.201901486 ↗
16. 10.1038/srep1522210.1038/srep15222 ↗
17. 10.1038/nbt.422610.1038/nbt.4226 ↗
18. 10.1186/s12987-019-0145-610.1186/s12987-019-0145-6 ↗
19. 10.1016/j.stem.2019.05.01110.1016/j.stem.2019.05.011 ↗
20. 10.1038/s41586-019-1506-710.1038/s41586-019-1506-7 ↗
21. 10.1016/j.cell.2007.11.01910.1016/j.cell.2007.11.019 ↗
22. 10.1038/nature1251710.1038/nature12517 ↗
23. 10.1038/s41593-020-00730-310.1038/s41593-020-00730-3 ↗
24. 10.1038/s41586-018-0858-810.1038/s41586-018-0858-8 ↗
25. 10.3389/fncel.2020.0013310.3389/fncel.2020.00133 ↗
26. 10.1016/j.stemcr.2019.05.02910.1016/j.stemcr.2019.05.029 ↗
27. 10.1016/j.stemcr.2017.01.02310.1016/j.stemcr.2017.01.023 ↗
28. 10.1038/s41598-018-19522-810.1038/s41598-018-19522-8 ↗
29. 10.1038/mp.2017.5610.1038/mp.2017.56 ↗
30. 10.1371/journal.pcbi.100379610.1371/journal.pcbi.1003796 ↗
31. 10.1186/s13041-015-0109-y10.1186/s13041-015-0109-y ↗
32. 10.1021/acsami.0c1059910.1021/acsami.0c10599 ↗
33. 10.1016/j.isci.2020.10143410.1016/j.isci.2020.101434 ↗
34. 10.1073/pnas.191613811610.1073/pnas.1916138116 ↗
35. 10.1021/acsami.8b0136510.1021/acsami.8b01365 ↗
36. 10.1038/nmeth.123610.1038/nmeth.1236 ↗
37. 10.1021/acsami.7b1786310.1021/acsami.7b17863 ↗
38. 10.1038/s41593-018-0175-410.1038/s41593-018-0175-4 ↗
39. 10.1002/jnr.2479410.1002/jnr.24794 ↗
40. 10.3389/fncel.2019.0023010.3389/fncel.2019.00230 ↗
41. 10.1080/21688370.2019.165115710.1080/21688370.2019.1651157 ↗
42. 10.1039/c6nr04545f10.1039/c6nr04545f ↗
43. 10.1039/c6tb00351f10.1039/c6tb00351f ↗
44. 10.1016/j.mee.2018.07.00510.1016/j.mee.2018.07.005 ↗
45. 10.1016/j.jneumeth.2015.01.02010.1016/j.jneumeth.2015.01.020 ↗
46. 10.1002/bit.2745810.1002/bit.27458 ↗
47. 10.1016/j.biomaterials.2014.04.02410.1016/j.biomaterials.2014.04.024 ↗
48. 10.1016/j.mee.2017.01.01210.1016/j.mee.2017.01.012 ↗
49. 10.1016/j.mee.2020.11140710.1016/j.mee.2020.111407 ↗
50. 10.3389/fnsyn.2018.0004510.3389/fnsyn.2018.00045 ↗
51. 10.1016/j.neuroscience.2018.11.01010.1016/j.neuroscience.2018.11.010 ↗
52. 10.1002/adma.20170568410.1002/adma.201705684 ↗
53. 10.1002/adhm.20200128410.1002/adhm.202001284 ↗
54. 10.1002/adhm.20170042610.1002/adhm.201700426 ↗
55. 10.1039/b9nr00243j10.1039/b9nr00243j ↗
56. 10.1016/j.biomaterials.2014.04.02410.1016/j.biomaterials.2014.04.024 ↗
57. 10.1016/j.nano.2016.12.02310.1016/j.nano.2016.12.023 ↗
58. 10.1039/c3tc31165a10.1039/c3tc31165a ↗
59. 10.1038/srep2376110.1038/srep23761 ↗
60. 10.1002/adhm.2017010610.1002/adhm.20170106 ↗
61. Gibson L. J. · 199710.1017/CBO9781139878326 ↗
62. 10.1016/s0376-7388(01)00552-x10.1016/s0376-7388(01)00552-x ↗
63. 10.1002/adhm.20190145410.1002/adhm.201901454 ↗
64. 10.1039/c6tb02246d10.1039/c6tb02246d ↗
65. 10.1016/j.tibtech.2019.04.00610.1016/j.tibtech.2019.04.006 ↗
66. 10.14336/AD.2020.010310.14336/AD.2020.0103 ↗
67. 10.1016/j.mee.2020.11137110.1016/j.mee.2020.111371 ↗