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Chen J, Zou X, Spencer DC, Morgan H. Single-cell electro-mechanical shear flow deformability cytometry. MICROSYSTEMS & NANOENGINEERING 2024; 10:173. [PMID: 39572527 PMCID: PMC11582679 DOI: 10.1038/s41378-024-00810-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 06/13/2024] [Accepted: 08/20/2024] [Indexed: 11/24/2024]
Abstract
The complex structural and molecular features of a cell lead to a set of specific dielectric and mechanical properties which can serve as intrinsic phenotypic markers that enable different cell populations to be characterised and distinguished. We have developed a microfluidic technique that exploits non-contact shear flow deformability cytometry to simultaneously characterise both the electrical and mechanical properties of single cells at high speed. Cells flow along a microchannel and are deformed (elongated) to different degrees by the shear force created by a viscoelastic fluid and channel wall. The electrical impedance of each cell is measured using sets of integrated microelectrodes along two orthogonal axes to determine the shape change and thus the electrical deformability, together with cell dielectric properties. The system performance was evaluated by measuring the electro-mechanical properties of cells treated in different ways, including osmotic shock, glutaraldehyde cross-linking and cytoskeletal disruption with Cytochalasin D and Latrunculin B. To confirm the accuracy of the system images of deformed cells were also captured using a camera. Correlation between the optical deformability and the electrical deformability is excellent. This novel cytometer has a throughput of ~100 cells s-1 is simple, does not use sheath flow or require high speed optical imaging.
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Affiliation(s)
- Junyu Chen
- School of Electronics and Computer Science, and Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK
| | - Xueping Zou
- School of Electronics and Computer Science, and Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK
| | - Daniel C Spencer
- School of Electronics and Computer Science, and Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK
| | - Hywel Morgan
- School of Electronics and Computer Science, and Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
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Chapman M, Rajagopal V, Stewart A, Collins DJ. Critical review of single-cell mechanotyping approaches for biomedical applications. LAB ON A CHIP 2024; 24:3036-3063. [PMID: 38804123 DOI: 10.1039/d3lc00978e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.
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Affiliation(s)
- Max Chapman
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
| | - Vijay Rajagopal
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
| | - Alastair Stewart
- ARC Centre for Personalised Therapeutics Technologies, The University of Melbourne, Parkville, VIC, Australia
- Department of Biochemistry and Pharmacology, The University of Melbourne, Parkville, VIC, Australia
| | - David J Collins
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia.
- Graeme Clarke Institute University of Melbourne Parkville, Victoria 3052, Australia
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Nguyen TH, Nguyen HA, Tran Thi YV, Hoang Tran D, Cao H, Chu Duc T, Bui TT, Do Quang L. Concepts, electrode configuration, characterization, and data analytics of electric and electrochemical microfluidic platforms: a review. Analyst 2023; 148:1912-1929. [PMID: 36928639 DOI: 10.1039/d2an02027k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/25/2023]
Abstract
Microfluidic cytometry (MC) and electrical impedance spectroscopy (EIS) are two important techniques in biomedical engineering. Microfluidic cytometry has been utilized in various fields such as stem cell differentiation and cancer metastasis studies, and provides a simple, label-free, real-time method for characterizing and monitoring cellular fates. The impedance microdevice, including impedance flow cytometry (IFC) and electrical impedance spectroscopy (EIS), is integrated into MC systems. IFC measures the impedance of individual cells as they flow through a microfluidic device, while EIS measures impedance changes during binding events on electrode regions. There have been significant efforts to improve and optimize these devices for both basic research and clinical applications, based on the concepts, electrode configurations, and cell fates. This review outlines the theoretical concepts, electrode engineering, and data analytics of these devices, and highlights future directions for development.
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Affiliation(s)
- Thu Hang Nguyen
- University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam.
| | | | - Y-Van Tran Thi
- University of Science, Vietnam National University, Hanoi, Vietnam.
| | | | - Hung Cao
- University of California, Irvine, USA
| | - Trinh Chu Duc
- University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam.
| | - Tung Thanh Bui
- University of Engineering and Technology, Vietnam National University, Hanoi, Vietnam.
| | - Loc Do Quang
- University of Science, Vietnam National University, Hanoi, Vietnam.
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Chen H, Guo J, Bian F, Zhao Y. Microfluidic technologies for cell deformability cytometry. SMART MEDICINE 2022; 1:e20220001. [PMID: 39188737 PMCID: PMC11235995 DOI: 10.1002/smmd.20220001] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 09/06/2022] [Indexed: 08/28/2024]
Abstract
Microfluidic detection methods for cell deformability cytometry have been regarded as powerful tools for single-cell analysis of cellular mechanical phenotypes, thus having been widely applied in the fields of cell preparation, separation, clinical diagnostics and so on. Featured with traits like easy operations, low cost and high throughput, such methods have shown great potentials on investigating physiological state and pathological changes during cellular deformation. Herein, a review on the advancements of microfluidic-based cell deformation cytometry is presented. We discuss several representative microfluidic-based cell deformability cytometry methods with their frontiers in practical applications. Finally, we analyze the current status and propose the remaining challenges with future perspectives and development directions.
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Affiliation(s)
- Hanxu Chen
- Department of Clinical LaboratoryNanjing Drum Tower HospitalSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjing, JiangsuChina
| | - Jiahui Guo
- Department of Clinical LaboratoryNanjing Drum Tower HospitalSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjing, JiangsuChina
| | - Feika Bian
- Department of Clinical LaboratoryNanjing Drum Tower HospitalSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjing, JiangsuChina
| | - Yuanjin Zhao
- Department of Clinical LaboratoryNanjing Drum Tower HospitalSchool of Biological Science and Medical EngineeringSoutheast UniversityNanjing, JiangsuChina
- Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health)Wenzhou InstituteUniversity of Chinese Academy of SciencesWenzhouZhejiangChina
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Liu Y, Fan Z, Qiao L, Liu B. Advances in microfluidic strategies for single-cell research. Trends Analyt Chem 2022. [DOI: 10.1016/j.trac.2022.116822] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Chen S, Zhang S, Zhu R. Computer-Vision-Based Dielectrophoresis Mobility Tracking for Characterization of Single-Cell Biophysical Properties. Anal Chem 2022; 94:14331-14339. [PMID: 36190245 DOI: 10.1021/acs.analchem.2c02935] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Fast and precise measurements of live single-cell biophysical properties is significant in disease diagnosis, cytopathologic analysis, etc. Existing methods still suffer from unsatisfied measurement accuracy and low efficiency. We propose a computer vision method to track cell dielectrophoretic movements on a microchip, enabling efficient and accurate measurement of biophysical parameters of live single cells, including cell radius, cytoplasm conductivity, and cell-specific membrane capacitance, and in situ extraction of cell texture features. We propose a prediction-iteration method to optimize the cell parameter measurement, achieving high accuracy (less than 0.79% error) and high efficiency (less than 30 s). We further propose a hierarchical classifier based on a support vector machine and implement cell classification using acquired cell physical parameters and texture features, achieving high classification accuracies for identifying cell lines from different tissues, tumor and normal cells, different tumor cells, different leukemia cells, and tumor cells with different malignancies. The method is label-free and biocompatible, allowing further live cell studies on a chip, e.g., cell therapy, cell differentiation, etc.
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Affiliation(s)
- Shengjie Chen
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Shengsen Zhang
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing100084, China
| | - Rong Zhu
- State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing100084, China
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