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Laminin-coated electronic scaffolds with vascular topography for tracking and promoting the migration of brain cells after injury

Nature Biomedical Engineering volume 7, pages 1282–1292 (2023)Cite this article

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Abstract

In the adult brain, neural stem cells are largely restricted into spatially discrete neurogenic niches, and hence areas of neuron loss during neurodegenerative disease or following a stroke or traumatic brain injury do not typically repopulate spontaneously. Moreover, understanding neural activity accompanying the neural repair process is hindered by a lack of minimally invasive devices for the chronic measurement of the electrophysiological dynamics in damaged brain tissue. Here we show that 32 individually addressable platinum microelectrodes integrated into laminin-coated branched polymer scaffolds stereotaxically injected to span a hydrogel-filled cortical lesion and deeper regions in the brains of mice promote neural regeneration while allowing for the tracking of migrating host brain cells into the lesion. Chronic measurements of single-unit activity and neural-circuit analyses revealed the establishment of spiking activity in new neurons in the lesion and their functional connections with neurons deeper in the brain. Electronic implants mimicking the topographical and surface properties of brain vasculature may aid the stimulation and tracking of neural-circuit restoration following injury.

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Fig. 1: Experimental design for vasculature-like electronics as migratory scaffolds for brain regeneration.
Fig. 2: Migration of newborn neurons from SVZ into the cortical resection along the VasES.
Fig. 3: Emergence of functionally active newborn neurons in the cortical resection.
Fig. 4: Neurons migrated into the cortical resection are involved in circuit rewiring.

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Data availability

The data supporting the results in this study are available within the paper and its Supplementary Information. Source data are available in the Harvard Dataverse with the identifier https://doi.org/10.7910/DVN/4HIWCA.

Code availability

The custom code used in this study is available at https://github.com/XiaoYangPhD/Yang_2023_NBME.

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Acknowledgements

The authors gratefully acknowledge S. Badylak, M. Murdock and Y.v.d. Merwe, who provided useful discussions and crucial insights for the generation and evaluation of the brain resection model at the initial stage of this work. We thank the assistance from J. Lee for the cross-correlation analysis, A. Zhang for the functionalization–stability characterization, T. Gao for electrophysiology recording instrumentation and T.-M. Fu for helpful discussions during the initial stages of this work. We thank Z. Ou, S. Zhao, X. Wu, G. Woods, and J. Shadrach for assistance with animal surgeries and vibratome sectioning. C.M.L. discloses support for the research described in this study from the National Institute on Drug Abuse (1R21DA043985-01) and the Director’s Pioneer Award (1DP1EB025835-01) of the National Institutes of Health. N.J.R. discloses support from a Stanford Bio-X Honorary Graduate Student Fellowship and the National Science Foundation Graduate Research Fellowship Program (DGE-1656518). This work was performed in part at the Harvard Center for Biological Imaging and Harvard University Center for Nanoscale Systems, a member of the National Nanotechnology Coordinated Infrastructure Network supported by the National Science Foundation.

Author information

Author notes

  1. Yue Qi

    Present address: Beijing Graphene Institute, Beijing, China

  2. Chonghe Wang

    Present address: Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

  3. Theodore J. Zwang

    Present address: Department of Neurology, MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Charlestown, MA, USA

  4. Charles M. Lieber

    Present address: Lieber Research Group, Lexington, MA, USA

  5. These authors contributed equally: Xiao Yang, Yue Qi.

Authors and Affiliations

  1. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA

    Xiao Yang, Yue Qi, Theodore J. Zwang & Charles M. Lieber

  2. Department of Psychiatry and Behavioral Sciences and Department of Chemistry, Stanford University, Stanford, CA, USA

    Xiao Yang

  3. John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

    Chonghe Wang & Charles M. Lieber

  4. Department of Applied Physics, Stanford University, Stanford, CA, USA

    Nicholas J. Rommelfanger

  5. Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA

    Guosong Hong

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Contributions

X.Y. and C.M.L. designed the experiments. X.Y. performed experiments including device fabrication, surface functionalization, animal surgeries, histology and electrophysiology. Y.Q. performed experiments including device fabrication, surface functionalization and histology at Harvard University. C.W. contributed to schematic illustrations and figure designs. T.J.Z. helped establish the surface functionalization and histology protocols. N.J.R. performed the finite-element simulations. G.H. helped establish the system and provided feedback. X.Y., Y.Q., C.W. and C.M.L. analysed the data. X.Y. and C.M.L. wrote the paper. All authors discussed the results, revised or commented on the manuscript.

Corresponding authors

Correspondence to Xiao Yang, Guosong Hong or Charles M. Lieber.

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Nature Biomedical Engineering thanks Eric Glowacki, Jacob Robinson, Darren Svirskis and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Photographs and schematics illustrating the processes of brain resection surgery and VasES implantation.

In each panel, I, II and III show photographs, top view schematics and side view schematics, respectively. a, Generate a cranial window centered at bregma with a lateral dimension of 4 mm (mediolateral) by 2 mm (anteroposterior). b, Resect cortical tissue to the depth of 1 mm in each hemisphere, leaving behind the resection cavity and intact margins of dura. c, Fill the resection with Matrigel and let it sit for 10–15 min to solidify. d, Stereotaxically implant VasES throughout the cortical resection, remaining cortical tissue and SVZ. Bond the input-output interface of electronics to flat flexible cable for electrophysiology recording. e, Seal the cranial window with agarose, silicone adhesive and dental cement sequentially. Scale bars, 2 mm.

Extended Data Fig. 2 Efficacy of VasES in directing the migration of SVZ newborn neurons by histology assessment.

a, b, and c represent control probe, VasES without laminin, and VasES, respectively. I, II and III show topographical design, surface functionalization and fluorescence images, respectively, at 1 week post-implantation. The insets feature larger area images, with the SVZ and the volumes used for quantification of DCX intensity outlined by white and yellow contours, respectively. Scale bars, 100 µm. d, Comparison of normalized DCX fluorescence intensity within 60 µm from control probes (N = 4), VasES without laminin functionalization (N = 3), and VasES with laminin functionalization (N = 3) at 1 week post-injection (details in the Supplementary Note 3). Independent samples were collected from different mice for each group. Error bars represent ±1 s.d. **P = 1.02 × 10−3 (control versus VasES), *P = 1.61 × 10−2 (control versus VasES without laminin), *P = 1.70 × 10−2 (VasES without laminin versus VasES); two-tailed t-test.

Extended Data Fig. 3 Evaluation of VasES by electrophysiology recording.

Representative multiplexed electrophysiology recordings of control probe (a) and VasES (b) at 7 (I) and 14 (II) days post-implantation. Scale bars, 100 ms (lateral) and 100 µV (vertical). c, Bar chart of chronic electrophysiology recording signal-to-noise ratios (SNRs) of control probe and VasES (details in the Supplementary Note 2), showing that VasES has higher SNRs than control probe on 4–14 days post-implantation. Data includes 77 channels from 3 control probes and 69 channels from 3 VasES probes. Left to right, P = 0.316, **P = 1.63 × 10−3, **P = 8.28 × 10−3, **P = 4.51 × 10−3; two-tailed t-test. Bars represent mean values.

Extended Data Fig. 4 Histology characterization of migration of newborn neurons.

a, An overview fluorescence image of control brain resection of which Fig. 2a is derived from, showing the relative position of the cortical resection with respect to SVZ. Scale bar, 200 µm. b, DCX fluorescence intensity profile along VasES in the resection as a function of the distance from the resection boundary (normalized against the intensity at the resection border; details in the Supplementary Note 3). c, Fluorescence image shown in Fig. 2c is displayed at a larger scale (I) and the corresponding DCX channel of the same image (II). The DCX data shows that the leading processes of the newborn neurons are closely associated and aligned with the VasES structural elements. d, Close-up fluorescence image captured at a higher resolution on the sample shown in Fig. 2c, showing the characteristic DCX morphology. e, Distribution of angle between leading processes of DCX+ newborn neurons and VasES structures (N = 87). f, Fluorescence image of implantation of control probe into the resection at 1 week post-implantation. The gray curve delineates the resection boundary. g, Fluorescence image of VasES implantation into cortical resection without insertion into the SVZ at 1 week post-implantation. The gray curve delineates the resection boundary. h, Quantitative analysis of normalized DCX fluorescence intensity at 0–60 μm near control probes (N = 3 independent samples; ‘control probe resection’) and near VasES without insertion into the SVZ (N = 3 independent samples; ‘VasES resection - SVZ’) at 1 week post-implantation (details in the Supplementary Note 3). The quantification of VasES implantation in the resection (‘VasES resection’), as presented in Fig. 2e, is also replicated here for comparison. ***P = 7.84 × 10−4 (VasES resection versus control probe resection), ***P = 3.80 × 10−4 (VasES resection versus VasES resection - SVZ), two-tailed t-test. Error bars reflect ±1 s.d. Scale bars, 50 µm for c and d, 300 µm for f and g.

Extended Data Fig. 5 Migration of astrocytes along VasES into cortical resection.

Optical microscope image (a) and fluorescence image (b) of the same field of view of VasES-implanted tissue at 1 week post-implantation. c, Zoomed-in image of the magenta dashed box in b, showing the migration of astrocytes into the resection. d, Close-up image of the cyan dashed box in c. The white asterisks highlight the alignment of migrating astrocytes with VasES elements. The black and white curves delineate the resection boundary. Scale bars, 200 µm for a and b, 50 µm for c, 20 µm for d.

Extended Data Fig 6 Histology characterization of tomato lectin+ cells and neurofilaments.

a and b, Infiltration of tomato lectin (TL)-positive endothelial cells and microglia into the cortical resection at 1 week (a) and 2 weeks (b) post-implantation. c and d, Infiltration of neurofilaments into the cortical resection at 4 weeks (c) and 3 months (d) post-implantation. The white dashed curves delineate the resection boundary. Scale bars, 100 µm.

Extended Data Fig 7 Histology characterization of NeuN+ neuronal nuclei in the cortical resection.

a–c, Fluorescence images showing the development of newborn neurons at 4 weeks post-implantation. Scale bars, 100 µm. Colocalization quantification shows that 99.0% of NeuN+ cells in cortical resection are DAPI+, demonstrating that the NeuN immunostaining is highly specific, and that false positive staining is largely excluded. d, Quantitative analysis of normalized NeuN fluorescence intensity within 60 µm from VasES elements at 4 weeks post-implantation on N = 6 independent samples. Error bar represents ±1 s.d. The normalized NeuN intensity is calculated as the ratio of the average fluorescence intensity within 60 μm from VasES versus the baseline value as the average fluorescence intensity 340–400 μm away. e, Normalized NeuN intensity along VasES probes in the cortical resection versus NeuN intensity in the undamaged native tissue. This is calculated as the ratio of the average fluorescence intensity along the VasES versus the average fluorescence intensity in the undamaged native tissue. Error bar represents ±1 s.d.

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Yang, X., Qi, Y., Wang, C. et al. Laminin-coated electronic scaffolds with vascular topography for tracking and promoting the migration of brain cells after injury. Nat. Biomed. Eng 7, 1282–1292 (2023). https://doi.org/10.1038/s41551-023-01101-6

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