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Yang J, Gu Y, Zhang C, Zhang Y, Liang W, Hao L, Zhao Y, Liu L, Wang W. Label-free purification and characterization of optogenetically engineered cells using optically-induced dielectrophoresis. LAB ON A CHIP 2022; 22:3687-3698. [PMID: 35903981 DOI: 10.1039/d2lc00512c] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Optogenetically engineered cell population obtained by heterogeneous gene expression plays a vital role in life science, medicine, and biohybrid robotics, and purification and characterization are essential to enhance its application performance. However, the existing cell purification methods suffer from complex sample preparation or inevitable damage and pollution. The efficient and nondestructive label-free purification and characterization of the optogenetically engineered cells, HEK293-ChR2 cells, is provided here using an optically-induced dielectrophoresis (ODEP)-based approach. The distinctive crossover frequencies of the engineered cells and the unmodified cells enable effective separation due to the opposite DEP forces on them. The ODEP-based approach can greatly improve the purity of the separated cell population and especially, the ratio of the engineered cells in the separated cell population can be enhanced by 275% at a low transfection rate. The size and the membrane capacitance of the separated cell population decreases and increases, respectively, as the ratio of the engineered cells grows in the cell population, indicating that successful expression of ChR2 in a single HEK293 cell makes its size and membrane capacitance smaller and larger, respectively. The results of biohybrid imaging with the optogenetically engineered cells demonstrated that cell purification can improve the imaging quality. This work proves that the separation and purification of engineered cells are of great significance for their application in practice.
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Affiliation(s)
- Jia Yang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanyu Gu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
- School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China.
| | - Chuang Zhang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Yuzhao Zhang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenfeng Liang
- School of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China
| | - Lina Hao
- School of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, China.
| | - Ying Zhao
- Department of General Surgery, Shengjing Hospital of China Medical University, Shenyang, 110004, China.
| | - Lianqing Liu
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
| | - Wenxue Wang
- State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China.
- Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
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Gheorghiu M, Polonschii C, Popescu O, Gheorghiu E. Advanced Optogenetic-Based Biosensing and Related Biomaterials. MATERIALS 2021; 14:ma14154151. [PMID: 34361345 PMCID: PMC8347019 DOI: 10.3390/ma14154151] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/12/2021] [Accepted: 07/20/2021] [Indexed: 02/07/2023]
Abstract
The ability to stimulate mammalian cells with light, brought along by optogenetic control, has significantly broadened our understanding of electrically excitable tissues. Backed by advanced (bio)materials, it has recently paved the way towards novel biosensing concepts supporting bio-analytics applications transversal to the main biomedical stream. The advancements concerning enabling biomaterials and related novel biosensing concepts involving optogenetics are reviewed with particular focus on the use of engineered cells for cell-based sensing platforms and the available toolbox (from mere actuators and reporters to novel multifunctional opto-chemogenetic tools) for optogenetic-enabled real-time cellular diagnostics and biosensor development. The key advantages of these modified cell-based biosensors concern both significantly faster (minutes instead of hours) and higher sensitivity detection of low concentrations of bioactive/toxic analytes (below the threshold concentrations in classical cellular sensors) as well as improved standardization as warranted by unified analytic platforms. These novel multimodal functional electro-optical label-free assays are reviewed among the key elements for optogenetic-based biosensing standardization. This focused review is a potential guide for materials researchers interested in biosensing based on light-responsive biomaterials and related analytic tools.
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Affiliation(s)
- Mihaela Gheorghiu
- International Centre of Biodynamics, 1B Intrarea Portocalelor, 060101 Bucharest, Romania;
- Correspondence: (M.G.); (E.G.)
| | - Cristina Polonschii
- International Centre of Biodynamics, 1B Intrarea Portocalelor, 060101 Bucharest, Romania;
| | - Octavian Popescu
- Molecular Biology Center, Institute for Interdisciplinary Research in Bio-Nano-Sciences, Babes-Bolyai-University, 400084 Cluj-Napoca, Romania;
- Institute of Biology Bucharest, Romanian Academy, 296 Splaiul Independentei, 060031 Bucharest, Romania
| | - Eugen Gheorghiu
- International Centre of Biodynamics, 1B Intrarea Portocalelor, 060101 Bucharest, Romania;
- Correspondence: (M.G.); (E.G.)
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Abstract
Magnetic particle-based immunoassays are widely used in microbiology-related assays for both microbial capture, separation, analysis, and detection. Besides facilitating sample operation, the implementation of micro-to-nanometer scale magnetic beads as a solid support potentially shortens the incubation time (for magnetic immuno capture) from several hours to less than an hour. Analytical technologies based on magnetic beads offer a rapid, effective and inexpensive way to separate and concentrate the target analytes prior to detection. Magneto-immuno separation uses magnetic particles coated with specific antibodies to capture target microorganisms, bear the corresponding antigens, and subsequently separate them from the sample matrix in a magnetic field. The method has been proven effective in separating various types of pathogenic bacteria from environmental water samples and in eliminating background interferences. Magnetic particles are often used to capture target cells (pathogenic bacteria) from samples. In most commercially available assays, the actual identification and quantitation of the captured cells is then performed by classical microbiological assays. This review highlights the most sensitive analytic methods (i.e., long-range surface plasmon resonance and electrochemical impedance spectroscopy) to detect magnetically tagged bacteria in conjunction with magnetic actuation.
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Affiliation(s)
- Eugen Gheorghiu
- International Centre of Biodynamics, Bucharest 060101, Romania
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Gheorghiu M. A short review on cell-based biosensing: challenges and breakthroughs in biomedical analysis. J Biomed Res 2020; 35:255-263. [PMID: 33888671 PMCID: PMC8383170 DOI: 10.7555/jbr.34.20200128] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 10/13/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022] Open
Abstract
Current cell-based biosensors have progressed substantially from mere alternatives to molecular bioreceptors into enabling tools for interfacing molecular machineries and gene circuits with microelectronics and for developing groundbreaking sensing and theragnostic platforms. The recent literature concerning whole-cell biosensors is reviewed with an emphasis on mammalian cells, and the challenges and breakthroughs brought along in biomedical analyses through novel biosensing concepts and the synthetic biology toolbox. These recent innovations allow development of cell-based biosensing platforms having tailored performances and capable to reach the levels of sensitivity, dynamic range, and stability suitable for high analytic/medical relevance. They also pave the way for the construction of flexible biosensing platforms with utility across biological research and clinical applications. The work is intended to stimulate interest in generation of cell-based biosensors and improve their acceptance and exploitation.
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Affiliation(s)
- Mihaela Gheorghiu
- Biosensors Department, International Centre of Biodynamics, Bucharest 060101, Romania
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