Abstract
Organoids are in vitro miniaturized cellular models of organs that offer opportunities for studying organ development, disease mechanisms and drug screening. Understanding the complex processes governing organoid development and function requires methods suitable for the continuous, long-term monitoring of cell activities (for example, electrophysiological and mechanical activity) at single-cell resolution throughout the entire three-dimensional (3D) structure. Cyborg organoid technology addresses this need by seamlessly integrating stretchable mesh nanoelectronics with tissue-like properties, such as tissue-level flexibility, subcellular feature size and mesh-like networks, into 3D organoids through a 2D-to-3D tissue reconfiguration process during organogenesis. This approach enables longitudinal, tissue-wide, single-cell functional mapping, thereby overcoming the limitations of existing techniques including recording duration, spatial coverage, and the ability to maintain stable contact with the tissue during organoid development. This protocol describes the fabrication and characterization of stretchable mesh nanoelectronics, their electrical performance, their integration with organoids and the acquisition of long-term functional organoid activity requiring multimodal data analysis techniques. Cyborg organoid technology represents a transformative tool for investigating organoid development and function, with potential for improving in vitro disease models, drug screening and personalized medicine. The procedure is suitable for users within a multidisciplinary team with expertise in stem cell biology, tissue engineering, nanoelectronics fabrication, electrophysiology and data science.
Key points
The procedure includes the fabrication of stretchable mesh nanoelectronics, the nanoelectronics’ integration within developing organoids and the long-term electrical measurements of organoid function.
Alternatives include imaging-based techniques, intracellular recordings and extracellular recordings using multielectrode arrays. Cyborg organoids provide stable 3D bioelectronics interfaces and enable the continuous monitoring of electrophysiological activity during development.
Access through your institution
Buy or subscribe
This is a preview of subscription content, access via your institution
Access options
Access through your institution
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Learn more
Subscribe to this journal
Receive 12 print issues and online access
$259.00 per year
only $21.58 per issue
Learn more
Buy this article
Purchase on SpringerLink
Instant access to full article PDF
Buy now
Prices may be subject to local taxes which are calculated during checkout
Additional access options:
Log in
Learn about institutional subscriptions
Read our FAQs
Contact customer support
Fig. 1: Overview of the cyborg organoid protocol.
Fig. 2: Fabrication of tissue-level flexible and stretchable mesh nanoelectronics.
Fig. 3: Packaging and characterization of stretchable mesh nanoelectronics.
Fig. 4: Integration of hPSCs-derived progenitors with mesh nanoelectronics.
Fig. 5: Long-term electrophysiological recording of cyborg organoids.
Fig. 6: Integrative data analysis strategies of cyborg organoids.
Data availability
The authors declare that the main data discussed in this protocol are available in the supporting primary research papers (https://doi.org/10.1021/acs.nanolett.9b02512, https://doi.org/10.1002/adma.202106829, https://doi.org/10.1126/sciadv.ade8513, and https://doi.org/10.1016/j.cell.2023.03.023, https://doi.org/10.1101/2024.03.18.585551).
References
Kim, J., Koo, B. K. & Knoblich, J. A. Human organoids: model systems for human biology and medicine. Nat. Rev. Mol. Cell. Biol. 21, 571–584 (2020).
CASPubMedPubMed CentralGoogle Scholar
Zhao, Z. et al. Organoids. Nat. Rev. Methods Primers 2, 94 (2022).
CASPubMedPubMed CentralGoogle Scholar
Li, Q. et al. Cyborg organoids: implantation of nanoelectronics via organogenesis for tissue-wide electrophysiology. Nano Lett. 19, 5781–5789 (2019).
CASPubMedGoogle Scholar
Le Floch, P. et al. Stretchable mesh nanoelectronics for 3D single-cell chronic electrophysiology from developing brain organoids. Adv. Mater. 34, e2106829 (2022).
PubMedPubMed CentralGoogle Scholar
Lin, Z. et al. Tissue-embedded stretchable nanoelectronics reveal endothelial cell-mediated electrical maturation of human 3D cardiac microtissues. Sci. Adv. 9, eade8513 (2023).
CASPubMedPubMed CentralGoogle Scholar
Li, Q. et al. Multimodal charting of molecular and functional cell states via in situ electro-sequencing. Cell 186, 2002–2017 e2021 (2023).
CASPubMedPubMed CentralGoogle Scholar
Wurst, W. & Bally-Cuif, L. Neural plate patterning: upstream and downstream of the isthmic organizer. Nat. Rev. Neurosci. 2, 99–108 (2001).
CASPubMedGoogle Scholar
Harvey, R. P. Patterning the vertebrate heart. Nat. Rev. Genet. 3, 544–556 (2002).
CASPubMedGoogle Scholar
Li, Q. et al. Cyborg islets: implanted flexible electronics reveal principles of human islet electrical maturation. Preprint at bioRxiv 2024.2003.2018.585551 (2024).
Tian, B. et al. Macroporous nanowire nanoelectronic scaffolds for synthetic tissues. Nat. Mater. 11, 986–994 (2012).
CASPubMedPubMed CentralGoogle Scholar
Liu, J. et al. Syringe-injectable electronics. Nat Nanotechnol. 10, 629–636 (2015).
CASPubMedPubMed CentralGoogle Scholar
Kim, D. H., Ghaffari, R., Lu, N. & Rogers, J. A. Flexible and stretchable electronics for biointegrated devices. Annu. Rev. Biomed. Eng. 14, 113–128 (2012).
CASPubMedGoogle Scholar
Tang, X., Shen, H., Zhao, S., Li, N. & Liu, J. Flexible brain–computer interfaces. Nat. Electron. 6, 109–118 (2023).
Google Scholar
Fan, J. A. et al. Fractal design concepts for stretchable electronics. Nat. Commun. 5, 3266 (2014).
PubMedGoogle Scholar
Xu, S. et al. Assembly of micro/nanomaterials into complex, three-dimensional architectures by compressive buckling. Science 347, 154–159 (2015).
CASPubMedGoogle Scholar
Feiner, R. et al. Engineered hybrid cardiac patches with multifunctional electronics for online monitoring and regulation of tissue function. Nat. Mater. 15, 679–685 (2016).
CASPubMedPubMed CentralGoogle Scholar
Feiner, R. & Dvir, T. Tissue–electronics interfaces: from implantable devices to engineered tissues. Nat. Rev. Mater. 3, 17076 (2017).
Google Scholar
Fu, T. M., Hong, G., Viveros, R. D., Zhou, T. & Lieber, C. M. Highly scalable multichannel mesh electronics for stable chronic brain electrophysiology. Proc. Natl Acad. Sci. USA 114, E10046–E10055 (2017).
CASPubMedPubMed CentralGoogle Scholar
Gao, H. et al. Graphene-integrated mesh electronics with converged multifunctionality for tracking multimodal excitation-contraction dynamics in cardiac microtissues. Nat. Commun. 15, 2321 (2024).
CASPubMedPubMed CentralGoogle Scholar
Quadrato, G., Brown, J. & Arlotta, P. The promises and challenges of human brain organoids as models of neuropsychiatric disease. Nat. Med. 22, 1220–1228 (2016).
CASPubMedGoogle Scholar
Smirnova, L. Biocomputing with organoid intelligence. Nat. Rev. Bioeng. 2, 633–634 (2024).
CASGoogle Scholar
Kagan, B. J. et al. In vitro neurons learn and exhibit sentience when embodied in a simulated game-world. Neuron 110, 3952–3969 e3958 (2022).
CASPubMedPubMed CentralGoogle Scholar
Cai, H. et al. Brain organoid reservoir computing for artificial intelligence. Nat. Electron. 6, 1032–1039 (2023).
Google Scholar
Chung, W. G. et al. Recent advances in electrophysiological recording platforms for brain and heart organoids. Adv. NanoBiomed Res. 2, 2200081 (2022).
CASGoogle Scholar
Richards, D. J. et al. Human cardiac organoids for the modelling of myocardial infarction and drug cardiotoxicity. Nat. Biomed. Eng. 4, 446–462 (2020).
CASPubMedPubMed CentralGoogle Scholar
Sakaguchi, H. et al. Self-organized synchronous calcium transients in a cultured human neural network derived from cerebral organoids. Stem Cell Reports 13, 458–473 (2019).
CASPubMedPubMed CentralGoogle Scholar
Yamamoto, Y., Hirose, S., Wuriyanghai, Y., Yoshinaga, D. & Makiyama, T. Electrophysiological analysis of hiPSC-derived cardiomyocytes using a patch-clamp technique. Methods Mol. Biol. 2320, 121–133 (2021).
CASPubMedGoogle Scholar
Xiang, Y. et al. Fusion of regionally specified hPSC-derived organoids models human brain development and interneuron migration. Cell Stem Cell 21, 383–398 e387 (2017).
CASPubMedPubMed CentralGoogle Scholar
Lewis-Israeli, Y. R. et al. Self-assembling human heart organoids for the modeling of cardiac development and congenital heart disease. Nat. Commun. 12, 5142 (2021).
CASPubMedPubMed CentralGoogle Scholar
Negraes, P. D. et al. Altered network and rescue of human neurons derived from individuals with early-onset genetic epilepsy. Mol. Psychiatry 26, 7047–7068 (2021).
PubMedPubMed CentralGoogle Scholar
Velasco, S. et al. Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature 570, 523–527 (2019).
CASPubMedPubMed CentralGoogle Scholar
Di Lullo, E. & Kriegstein, A. R. The use of brain organoids to investigate neural development and disease. Nat. Rev. Neurosci. 18, 573–584 (2017).
PubMedPubMed CentralGoogle Scholar
Chung, J. E. et al. A fully automated approach to spike sorting. Neuron 95, 1381–1394 e1386 (2017).
CASPubMedPubMed CentralGoogle Scholar
Pachitariu, M., Sridhar, S., Pennington, J. & Stringer, C. Spike sorting with Kilosort4. Nat Methods 21, 914–921 (2024).
CASPubMedPubMed CentralGoogle Scholar
Saelens, W., Cannoodt, R., Todorov, H. & Saeys, Y. A comparison of single-cell trajectory inference methods. Nat. Biotechnol. 37, 547–554 (2019).
CASPubMedGoogle Scholar
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 e3529 (2021).
CASPubMedPubMed CentralGoogle Scholar
Lian, X. et al. Directed cardiomyocyte differentiation from human pluripotent stem cells by modulating Wnt/beta-catenin signaling under fully defined conditions. Nat. Protoc. 8, 162–175 (2013).
CASPubMedGoogle Scholar
Lian, X. et al. Robust cardiomyocyte differentiation from human pluripotent stem cells via temporal modulation of canonical Wnt signaling. Proc. Natl Acad. Sci. USA 109, E1848–E1857 (2012).
CASPubMedPubMed CentralGoogle Scholar
Yoon, S. J. et al. Reliability of human cortical organoid generation. Nat. Methods 16, 75–78 (2019).
CASPubMedGoogle Scholar
Pollock, S. D., Galicia-Silva, I. M., Liu, M., Gruskin, Z. L. & Alvarez-Dominguez, J. R. Scalable generation of 3D pancreatic islet organoids from human pluripotent stem cells in suspension bioreactors. STAR Protoc. 4, 102715 (2023).
CASPubMedPubMed CentralGoogle Scholar
Alvarez-Dominguez, J. R. et al. Circadian entrainment triggers maturation of human in vitro islets. Cell Stem Cell 26, 108–122 e110 (2020).
CASPubMedGoogle Scholar
Buccino, A. P. et al. SpikeInterface, a unified framework for spike sorting. Elife 9, e61834 (2020).
CASPubMedPubMed CentralGoogle Scholar
McInnes, L., Healy, J. & Melville, J. UMAP: uniform manifold approximation and projection for dimension reduction. Preprint at https://arxiv.org/abs/1802.03426 (2018).
Moon, K. R. et al. Visualizing structure and transitions in high-dimensional biological data. Nat. Biotechnol. 37, 1482–1492 (2019).
CASPubMedPubMed CentralGoogle Scholar
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
CASPubMedPubMed CentralGoogle Scholar
Street, K. et al. Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics. BMC Genomics 19, 477 (2018).
PubMedPubMed CentralGoogle Scholar
Gala, R. et al. Consistent cross-modal identification of cortical neurons with coupled autoencoders. Nat. Comput. Sci. 1, 120–127 (2021).
PubMedPubMed CentralGoogle Scholar
Liu, R. et al. An AI-cyborg system for adaptive intelligent modulation of organoid maturation. Preprint at bioRxivhttps://doi.org/10.1101/2024.12.07.627355 (2024).
Download references
Acknowledgements
We acknowledge the valuable discussions with A.ML., X.Z. and H.S. J.Liu acknowledges the support of NIH/NIMH 1RF1MH123948; NIH/NIDDK 1DP1DK130673; NSF/ECCS-2038603; NIH/NLM 5R01LM014465.
Author information
Author notes
These authors contributed equally: Zuwan Lin, Wenbo Wang, Ren Liu, Qiang Li.
Authors and Affiliations
John A. Paulson School of Engineering and Applied Sciences, Harvard University, Boston, MA, USA
Zuwan Lin, Wenbo Wang, Ren Liu, Qiang Li, Jaeyong Lee, Charles Hirschler & Jia Liu
Broad Institute of MIT and Harvard, Cambridge, MA, USA
Zuwan Lin & Wenbo Wang
Authors
Zuwan Lin
View author publications
You can also search for this author inPubMedGoogle Scholar
2. Wenbo Wang
View author publications
You can also search for this author inPubMedGoogle Scholar
3. Ren Liu
View author publications
You can also search for this author inPubMedGoogle Scholar
4. Qiang Li
View author publications
You can also search for this author inPubMedGoogle Scholar
5. Jaeyong Lee
View author publications
You can also search for this author inPubMedGoogle Scholar
6. Charles Hirschler
View author publications
You can also search for this author inPubMedGoogle Scholar
7. Jia Liu
View author publications
You can also search for this author inPubMedGoogle Scholar
Contributions
Z.L., W.W., R.L., Q.L. and J.Liu. developed the protocol and drafted the manuscript with input from C.H. and J.Lee. All authors read, edited and approved the final manuscript.
Corresponding author
Correspondence to Jia Liu.
Ethics declarations
Competing interests
J. Liu is a co-founder of Axoft, Inc.
Peer review
Peer review information
Nature Protocols thanks Gi Doo Cha and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Key references
Li, Q. et al. Nano Lett. 19, 5781–5789 (2019): https://doi.org/10.1021/acs.nanolett.9b02512
Lin, Z. et al. Sci. Adv. 9, eade8513 (2023): https://doi.org/10.1126/sciadv.ade8513
Li, Q. et al. Cell 186, 2002–2017 e2021 (2023): https://doi.org/10.1016/j.cell.2023.03.023
Le Floch, P. et al. Adv. Mater. 34, e2106829 (2022): https://doi.org/10.1002/adma.202106829
Supplementary information
Supplementary Information
Supplementary Figures 1-2.
Reporting Summary
Supplementary Data 1
Photomask of mesh nanoelectronics.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
Reprints and permissions
About this article
Check for updates. Verify currency and authenticity via CrossMark
Cite this article
Lin, Z., Wang, W., Liu, R. et al. Cyborg organoids integrated with stretchable nanoelectronics can be functionally mapped during development. Nat Protoc (2025). https://doi.org/10.1038/s41596-025-01147-7
Download citation
Received:04 August 2024
Accepted:31 December 2024
Published:26 March 2025
DOI:https://doi.org/10.1038/s41596-025-01147-7
Share this article
Anyone you share the following link with will be able to read this content:
Get shareable link
Sorry, a shareable link is not currently available for this article.
Copy to clipboard
Provided by the Springer Nature SharedIt content-sharing initiative