Modeling the detection of transient vesicular exocytotic release from single cells with cylindrical enzymatic nanoelectrodes

Amperometric electrochemical detection has proven to be an important versatile tool for studying transient single exocytotic events in tissues and single cells. Meanwhile, advances in electrode materials and microfabrication have enabled the routine fabrication of submicrometric electrochemical sensors for in vivo or in vitro analysis of single cells or organelles. In this context, cylindrical nanoelectrodes offer important advantages because their sensing elements can be driven across biological membranes or into intercellular clefts while preserving the biological processes being studied. However, their dimensions and curvatures are comparable to those of the releasing vesicles that deliver their stored material into the extracellular environment. The electrochemical currents are then determined not only by the kinetics of biological release, which is the main objective of monitoring, but also by the intricate diffusion patterns of the analytes in the nanoelectrode-cell space and the kinetics of their electrochemical detection. This situation becomes even more complex when the analytes are not directly electroactive on the electrode surface, but require mediation by an enzymatic process, preventing reliance on classical approaches. Consequently, a theoretical model has been developed to determine and quantify the consequences of these limitations on the electrochemical measurement of transient release processes in quantitative and kinetic terms.

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Publication Details

Journal
Electrochimica Acta
Published
2024-10-09
DOI
https://doi.org/10.1016/j.electacta.2024.145214
Citations
4
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
1.07

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article

Modeling the detection of transient vesicular exocytotic release from single cells with cylindrical enzymatic nanoelectrodes

Wei‐Hua Huang, Alexander Oleinick, Irina Svir, Christian Amatore et al.
4 citations
Electrochimica Acta
Neuroscience and Neural Engineering
1.07
article

Modeling the detection of transient vesicular exocytotic release from single cells with cylindrical enzymatic nanoelectrodes

Wei‐Hua Huang, Alexander Oleinick, Irina Svir, Christian Amatore, Reina Dannaoui
article en
4 citations

Abstract

Amperometric electrochemical detection has proven to be an important versatile tool for studying transient single exocytotic events in tissues and single cells. Meanwhile, advances in electrode materials and microfabrication have enabled the routine fabrication of submicrometric electrochemical sensors for in vivo or in vitro analysis of single cells or organelles. In this context, cylindrical nanoelectrodes offer important advantages because their sensing elements can be driven across biological membranes or into intercellular clefts while preserving the biological processes being studied. However, their dimensions and curvatures are comparable to those of the releasing vesicles that deliver their stored material into the extracellular environment. The electrochemical currents are then determined not only by the kinetics of biological release, which is the main objective of monitoring, but also by the intricate diffusion patterns of the analytes in the nanoelectrode-cell space and the kinetics of their electrochemical detection. This situation becomes even more complex when the analytes are not directly electroactive on the electrode surface, but require mediation by an enzymatic process, preventing reliance on classical approaches. Consequently, a theoretical model has been developed to determine and quantify the consequences of these limitations on the electrochemical measurement of transient release processes in quantitative and kinetic terms.

Electrochimica ActaVol. 508
Centre National de la Recherche Scientifique (FR), Xiamen University (CN), Université Paris Sciences et Lettres (FR), École Normale Supérieure - PSL (FR), Wuhan University (CN), Sorbonne Université (FR)
École Normale Supérieure, National Natural Science Foundation of China, Centre National de la Recherche Scientifique, Xiamen University, Sorbonne Université
Openalex Percentile: Top 24%
Neuroscience and Neural Engineering
1.07
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