Journal article
Perfusion double-channel micropipette probes for oxygen flux mapping with single-cell resolution
Beilstein journal of nanotechnology, v 9(1), pp 850-860
2018
PMID: 29600146
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Measuring cellular respiration with single-cell spatial resolution is a significant challenge, even with modern tools and techniques. Here, a double-channel micropipette is proposed and investigated as a probe to achieve this goal by sampling fluid near the point of interest. A finite element model (FEM) of this perfusion probe is validated by comparing simulation results with experimental results of hydrodynamically confined fluorescent molecule diffusion. The FEM is then used to investigate the dependence of the oxygen concentration variation and the measurement signal on system parameters, including the pipette's shape, perfusion velocity, position of the oxygen sensors within the pipette, and proximity of the pipette to the substrate. The work demonstrates that the use of perfusion double-barrel micropipette probes enables the detection of oxygen consumption signals with micrometer spatial resolution, while amplifying the signal, as compared to sensors without the perfusion system. In certain flow velocity ranges (depending on pipette geometry and configuration), the perfusion flow increases oxygen concentration gradients formed due to cellular oxygen consumption. An optimal perfusion velocity for respiratory measurements on single cells can be determined for different system parameters (e.g., proximity of the pipette to the substrate). The optimum perfusion velocities calculated in this paper range from 1.9 to 12.5 μm/s. Finally, the FEM model is used to show that the spatial resolution of the probe may be varied by adjusting the pipette tip diameter, which may allow oxygen consumption mapping of cells within tissue, as well as individual cells at subcellular resolution.
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Details
- Title
- Perfusion double-channel micropipette probes for oxygen flux mapping with single-cell resolution
- Creators
- Yang Gao - Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USABin Li - Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USARiju Singhal - Department of Material Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USAAdam Fontecchio - Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USABen Pelleg - Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USAZulfiya Orynbayeva - Department of Surgery, Drexel University, 245 N. 15th Street, Philadelphia, PA 19102, USAYury Gogotsi - Department of Material Science and Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USAGary Friedman - Department of Electrical and Computer Engineering, Drexel University, 3141 Chestnut Street, Philadelphia, PA 19104, USA
- Publication Details
- Beilstein journal of nanotechnology, v 9(1), pp 850-860
- Publisher
- Germany
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering; Materials Science and Engineering; Surgery
- Web of Science ID
- WOS:000427531400001
- Scopus ID
- 2-s2.0-85043482202
- Other Identifier
- 991014969853904721
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InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Web of Science research areas
- Materials Science, Multidisciplinary
- Nanoscience & Nanotechnology
- Physics, Applied