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Label-free robotic mitochondrial biopsy

  • Yanmei Ma (Co-first Author)
  • , Weikang Hu (Co-first Author)
  • , Muyang Ruan
  • , Feixiang Bao
  • , Xingguo Liu
  • , Dong Sun
  • , Hongri Gu*
  • , Chengzhi Hu*
  • *Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

6 Downloads (CityUHK Scholars)

Abstract

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. © 2025 the Authors, some rights reserved;
Original languageEnglish
Article numbereadx4289
JournalScience Advances
Volume11
Issue number43
Online published22 Oct 2025
DOIs
Publication statusPublished - Oct 2025

Funding

this work is supported by the national Key technologies R&d Program of china (grant no. 2023YFc2415900 to c.h.) and the national natural Science Foundation of china (no. 62373182 to c.h.). this work is partly supported by the Shenzhen Science and technology Program (grant no. JcYJ20241202125417024 to c.h.)and Guangdong Basic and Applied Basic Research Foundation (grant no. 2024A1515011915 to c.h.).

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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