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Khochare SD, Li X, Yang X, Shi Y, Feng G, Ruchhoeft P, Shih WC, Shan X. Functional Plasmonic Microscope: Characterizing the Metabolic Activity of Single Cells via Sub-nm Membrane Fluctuations. Anal Chem 2024; 96:5771-5780. [PMID: 38563229 DOI: 10.1021/acs.analchem.3c04301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Metabolic abnormalities are at the center of many diseases, and the capability to film and quantify the metabolic activities of a single cell is important for understanding the heterogeneities in these abnormalities. In this paper, a functional plasmonic microscope (FPM) is used to image and measure metabolic activities without fluorescent labels at a single-cell level. The FPM can accurately image and quantify the subnanometer membrane fluctuations with a spatial resolution of 0.5 μm in real time. These active cell membrane fluctuations are caused by metabolic activities across the cell membrane. A three-dimensional (3D) morphology of the bottom cell membrane was imaged and reconstructed with FPM to illustrate the capability of the microscope for cell membrane characterization. Then, the subnanometer cell membrane fluctuations of single cells were imaged and quantified with the FPM using HeLa cells. Cell metabolic heterogeneity is analyzed based on membrane fluctuations of each individual cell that is exposed to similar environmental conditions. In addition, we demonstrated that the FPM could be used to evaluate the therapeutic responses of metabolic inhibitors (glycolysis pathway inhibitor STF 31) on a single-cell level. The result showed that the metabolic activities significantly decrease over time, but the nature of this response varies, depicting cell heterogeneity. A low-concentration dose showed a reduced fluctuation frequency with consistent fluctuation amplitudes, while the high-concentration dose showcased a decreasing trend in both cases. These results have demonstrated the capabilities of the functional plasmonic microscope to measure and quantify metabolic activities for drug discovery.
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Affiliation(s)
- Suraj D Khochare
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Xiaoliang Li
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Xu Yang
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Yaping Shi
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Guangxia Feng
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Paul Ruchhoeft
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Wei-Chuan Shih
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
| | - Xiaonan Shan
- Advanced Imaging and Sensing Lab, Department of Electrical and Computer Engineering, University of Houston, Houston, Texas 77204, United States
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He Y, Xu P, Wu H, Chu Y, Zhang G. The model of electrified cell clusters in biological tissues basing on the resting potential difference. Medicine in Novel Technology and Devices 2023. [DOI: 10.1016/j.medntd.2023.100218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
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Riol A, Cervera J, Levin M, Mafe S. Cell Systems Bioelectricity: How Different Intercellular Gap Junctions Could Regionalize a Multicellular Aggregate. Cancers (Basel) 2021; 13:5300. [PMID: 34771463 DOI: 10.3390/cancers13215300] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 10/18/2021] [Accepted: 10/19/2021] [Indexed: 01/10/2023] Open
Abstract
Electric potential distributions can act as instructive pre-patterns for development, regeneration, and tumorigenesis in cell systems. The biophysical states influence transcription, proliferation, cell shape, migration, and differentiation through biochemical and biomechanical downstream transduction processes. A major knowledge gap is the origin of spatial patterns in vivo, and their relationship to the ion channels and the electrical synapses known as gap junctions. Understanding this is critical for basic evolutionary developmental biology as well as for regenerative medicine. We computationally show that cells may express connexin proteins with different voltage-gated gap junction conductances as a way to maintain multicellular regions at distinct membrane potentials. We show that increasing the multicellular connectivity via enhanced junction function does not always contribute to the bioelectrical normalization of abnormally depolarized multicellular patches. From a purely electrical junction view, this result suggests that the reduction rather than the increase of specific connexin levels can also be a suitable bioelectrical approach in some cases and time stages. We offer a minimum model that incorporates effective conductances ultimately related to specific ion channel and junction proteins that are amenable to external regulation. We suggest that the bioelectrical patterns and their encoded instructive information can be externally modulated by acting on the mean fields of cell systems, a complementary approach to that of acting on the molecular characteristics of individual cells. We believe that despite the limitations of a biophysically focused model, our approach can offer useful qualitative insights into the collective dynamics of cell system bioelectricity.
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