Robotic intracellular electrochemical sensing |  EurekAlert!

Robotic intracellular electrochemical sensing | EurekAlert!

Image: The intracellular sensing robot automatically performs quantitative measurements on multiple 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 sensing system, which provides a highly efficient approach to detect intrinsic cellular properties and heterogeneity for better investigation of disease progression or early diagnosis of disease. The new research paper was published on September 2 in the journal Cyborg and Bionic Systems.

Measuring biochemical processes within cells is important to quantitatively understanding the function of biological systems. Nano-pipette-based intracellular sensing is a non-destructive, in situ, label-free measurement method. However, the small size of the cells and the tip of the nanopipette make it difficult to perform the intracellular measurement efficiently by manual manipulation, which is an obstacle to accessing statistically significant data. Therefore, the researchers designed a highly efficient and consistent intracellular sensing system by integrating automation technology.

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

In addition, the team proposed a label-free cell detection algorithm, which can avoid the effect of fluorescent staining on cells and precisely locate the sites of penetration for high-efficiency intracellular measurement. The algorithm automatically moves cells to the defocusing level to increase the grayscale difference between adherent and background cells, thus simplifying cell detection and improving the cell recognition rate.

Besides, a non-bypassing nanopipette tip position was developed to avoid tip damage caused by tip collision with the cell dish during AF. Specifically, the normalized correlation coefficients during template matching at different positions of the z-axis were used as a focus metric to autofocus the pipette tip without overshoot and tip damage.

Moreover, proximity detection based on ionic current feedback was used to accurately determine the relative height between the nanopipette tip and the cell surface due to the highly varied thickness of adherent cells. When the tip of the nanopipette approaches the cell, the tip will be gradually blocked by the cell, and the ionic current through the tip opening will decrease. Therefore, the relative height between the edge and the cell can be measured accurately.

Finally, cell penetration and electrochemical detection of ROS by human breast cancer cells and zebrafish embryonic cells were evaluated, and the anisotropy of ROS signaling indicates that the system is capable of highly selective response to ROS and quantification of intracellular ROS.

This work provides a systematic approach to automated intracellular sensing of adherent cells, laying a solid foundation for the discovery, diagnosis, and classification of various forms of biochemical reactions within single cells. Besides, the proposed system will also have important applications in lineage tracing for development biology and high-resolution manipulation of organelles in living single cells to investigate the specific causes of diseases and develop new treatments.

The authors of the paper are 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 number JCYJ20190809144013494), and the Guangdong Science and Technology Program (grant number 2021A1515011813). This work is supported in part by the Shenzhen Municipal Science, Technology and Innovation Commission under grant no. ZDSYS20200811143601004 and partly by Guangdong Marine Science and Southern Engineering Laboratory (Guangdong). The authors acknowledge the assistance of SUSTech’s core research facilities. We thank Professor Dong Liu of the Department of Biology at Southern University of Science and Technology for providing zebrafish embryos.

The research paper titled “Robotic Intracellular Electrochemical Sensing of Adherent Cells” is published in the journal. Cyborg and Bionic Systems On September 2, 2022, at the DOI: https://doi.org/10.34133/2022/9763420

reference

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

Original paper title: Robotic intracellular electrochemical sensing of adherent cells

magazine: Cyborg and Bionic Systems

DOI: 10.34133/2022/9763420

Affiliations:

1 Shenzhen Key Laboratory for Biomimetic Robots 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 Universities Human Augmentation and Rehabilitation Robotics, Southern University of Science and Technology, Shenzhen, China

Brief introduction about author Dr. Hu Chengzhi.

Chengzhi Hu received his Ph.D. He received his Ph.D. from the Department of Nano-Micro Systems and Engineering at Nagoya University in 2014. He was a Postdoctoral Fellow at the Multi-Scale Robotics Laboratory at ETH Zurich between 2014 and 2018. Since 2018, he has been an Associate Professor in the University’s Department of Mechanics and Energy Engineering. Southern Science and Technology, China. He has been involved in the development of micro/nanobots, microfluidic chips, micro/nano instruments, and other bioMEMS devices for use in biological analysis and biomedical applications.

Personal home page: https://faculty.sustech.edu.cn/hucz/en/


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