Label-free robotic mitochondrial biopsy
Robotic micromanipulation has advanced cellular probing, yet achieving precise, minimally invasive intracellular operations without fluorescent labeling remains challenging. Fluorescent techniques often cause photodamage and cytotoxicity and interfere with downstream analyses. Here, we introduce an automated, multifunctional nanoprobing platform capable of label-free extraction of mitochondria from living cells with high spatiotemporal resolution. The nanoprobe integrates two individually addressable nanoelectrodes that perform electrochemical detection of reactive oxygen and nitrogen species, produced by mitochondrial metabolism, followed by dielectrophoretic trapping, manipulation, and extraction of mitochondria. We successfully demonstrated the extraction of mitochondria from living cells, which is validated through fluorescence labeling before and after extraction. Subsequent quantitative polymerase chain reaction further confirmed that the extracted sample contained mitochondria. The fusion of the transplanted mitochondria within the recipient cell's mitochondrial network confirms their activity. This automated, label-free, in situ organelle extraction micromanipulation system offers a powerful tool for understanding disease mechanisms linked to dysfunctional organelles and enables single-cell surgeries for organelle transplantation.
Authors
- Feixiang Bao (ORCID: https://orcid.org/0000-0002-6985-2602)
- Xingguo Liu (ORCID: https://orcid.org/0000-0001-7060-8204)
- Chengzhi Hu (ORCID: https://orcid.org/0000-0002-8627-2335)
- Hongri Gu (ORCID: https://orcid.org/0000-0002-6396-3408)
- Weikang Hu (ORCID: https://orcid.org/0000-0002-8315-7251)
- Dong Sun (ORCID: https://orcid.org/0000-0003-3945-4037)
- Yanmei Ma (ORCID: https://orcid.org/0000-0001-7941-7252)
- Muyang Ruan
Institutions
- City University of Hong Kong (HK)
- Chinese Academy of Sciences (CN)
- Hong Kong University of Science and Technology (HK)
- Guangzhou Institutes of Biomedicine and Health (CN)
- Southern University of Science and Technology (CN)
Publication Details
- Journal
- Science Advances
- Published
- 2025-10-22
- DOI
- https://doi.org/10.1126/sciadv.adx4289
- Citations
- 4
- Primary Topic
- Neuroscience and Neural Engineering
- Type
- article
- Field-Weighted Citation Impact
- 3.64