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Robotic Intracellular Electrochemical Detection | Eurek alert!

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image: The intracellular detection robot automatically performs quantitative measurements on several cells.
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Credit: Weikang Hu, Southern University of Science and Technology

A research team from Southern University of Science and Technology has developed an automated intracellular detection system, which provides a high-efficiency approach to revealing cellular intrinsic characteristics and heterogeneity for better investigation of disease progression or early diagnosis of the disease. The new research paper was published Sept. 2 in the journal Cyborg and bionic systems.

The measurement of intracellular biochemical processes is important for quantitatively understanding the function of biological systems. Intracellular detection by nanopipette is an in situ, label-free and non-destructive measurement method. However, the small size of the cells and the tip of the nanopipette make it difficult to efficiently perform intracellular measurements by manual manipulation, which poses a barrier to obtaining statistically significant data. Therefore, the researchers designed a highly efficient and consistent intracellular detection system by integrating automation technology.

First, the nanopipette-based sensor with a tip diameter of about 100 nm was designed, where a platinum ring on the tip of the nanopipette was used as a working electrode for the electrochemical detection of reactive species. oxygen (ROS). At the same time, the sensor was mounted on a high-precision micromanipulator with 5 nm motion resolution, and an inverted fluorescence microscope was used for visual feedback.

Additionally, the team proposed a label-free cell detection algorithm, which can avoid the influence of fluorescent staining on cells and precisely locate penetration sites for highly efficient intracellular measurement. The algorithm automatically moves cells to a defocus plane to maximize the grayscale difference between adherent cells and the background, thereby simplifying cell detection and improving cell recognition rate.

In addition, overshoot-free nanopipette tip positioning was developed to prevent tip damage caused by the tip colliding with the cell box during autofocus. Specifically, the normalized correlation coefficients when matching the templates at different z-axis positions were used as a focus metric to autofocus the nanopipette tip without tip overshoot or damage.

Furthermore, proximity sensing based on ion current feedback was used to accurately determine the relative height between the nanopipette tip and the cell surface due to the widely varying thickness of adherent cells. When the tip of the nanopipette approaches the cell, the tip will be gradually blocked by the cell and the ion current through the opening of the tip will decrease. Therefore, the relative height between the tip and the cell can be measured accurately.

Finally, cell penetration and electrochemical detection of ROS were assessed by human breast cancer cells and zebrafish embryo cells, and the variation in ROS signals indicates that the system is capable of a highly selective response to ROS and a quantitative measurement of intracellular ROS.

This work provides a systematic approach for automated intracellular detection of adherent cells, laying a solid foundation for high-throughput detection, diagnosis and classification of different forms of biochemical reactions within single cells. In addition, the proposed system will also have important applications in lineage tracing for developmental biology and high-resolution manipulation of organelles in living single cells to study specific causes of diseases and development of new therapies.

Authors of the article include Weikang Hu, Yanmei Ma, Zhen Zhan, Danish Hussain and Chengzhi Hu.

This work is supported by the National Natural Science Foundation of China (61903177), the Shenzhen Science and Technology Program (Grant No. JCYJ20190809144013494) and the Science and Technology Program of Guangdong (Grant No. 2021A1515011813). This work is supported in part by the Science, Technology and Innovation Commission of Shenzhen Municipality under grant number. ZDSYS20200811143601004 and in part by Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou). The authors acknowledge assistance from SUSTech Core Research Facilities. We thank Prof. Dong Liu from the Department of Biology, Southern University of Science and Technology for providing zebrafish embryos.

The article “Robotic Intracellular Electrochemical Sensing for Adherent Cells” was published in the journal Cyborg and bionic systems September 2, 2022, at DOI: https://doi.org/10.34133/2022/9763420

Reference

Authors: Weikang Hu1, Yanmei Ma1, Zhen Zhan1, Danish Hussain1,2 and Chengzhi Hu1,3*

Title of the original article: Robotic intracellular electrochemical sensing for adherent cells

Log: Cyborg and bionic systems

DOI: 10.34133/2022/9763420

Memberships:

1 Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, China

2 Department of Mechatronics Engineering, National University of Science and Technology, Islamabad, Pakistan

3 Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, China

A brief introduction about the author Dr. Hu Chengzhi.

Chengzhi Hu obtained his doctorate. graduated from the Department of Micro-Nano Systems and Engineering at Nagoya University in 2014. He was a postdoctoral associate at the Multi-Scale Robotics Lab at ETH Zurich between 2014 and 2018. Since 2018, he has been an associate professor at the Department of Mechanics and Power Engineering at Southern University of Science and Technology, China. It has engaged in the development of micro-/nano-robots, microfluidic chips, micro-/nano-tools and other bioMEMS devices for biological analysis and biomedical applications.

Personal homepage: https://faculty.sustech.edu.cn/hucz/en/


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