Computational Model of Electrode-Induced Microenvironmental Effects on pH Measurements Near a Cell Membrane
Author(s) -
Daniela Calvetti,
J. Prezioso,
Rossana Occhipinti,
Walter F. Boron,
Erkki Somersalo
Publication year - 2020
Publication title -
multiscale modeling and simulation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.037
H-Index - 70
eISSN - 1540-3467
pISSN - 1540-3459
DOI - 10.1137/19m1262875
Subject(s) - membrane , electrode , diffusion , discretization , biophysics , chemistry , biological system , mechanics , chemical physics , materials science , physics , thermodynamics , biochemistry , biology , mathematics , mathematical analysis
The mechanism of gas transport across cell membranes remains a topic of considerable interest, particularly regarding the extent to which lipids vs. specific membrane proteins provide conduction pathways. Studies of transmembrane (CO 2 ) transport often rely on data collected under controlled conditions, using pH-sensitive microelectrodes at the extracellular surface to record changes due to extracellular CO 2 diffusion and reactions. Although recent detailed computational models can predict a qualitatively correct behavior, a mismatch between the dynamical ranges of the predicted and observed pH curves raises the question whether the discrepancy may be due to a bias introduced by the pH electrode itself. More specifically, it is reasonable to ask whether bringing the electrode tip near or in contact with the membrane creates a local microenvironment between the electrode tip and the membrane, so that the measured data refer to the microenvironment rather than to the free surface. Here, we introduce a detailed computational model, designed to address this question. We find that, as long as a zone of free diffusion exists between the tip and the membrane, the microenvironment behaves effectively as the free membrane. However, according to our model, when the tip contacts the membrane, partial quenching of extracellular diffusion by the electrode rim leads to a significant increase in the pH dynamics under the electrode, matching values measured in physiological experiments. The computational schemes for the model predictions are based on semi-discretization by a finite-element method, and an implicit-explicit time integration scheme to capture the different time scales of the system.
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