Ultrasensitive liposome-based assay for the quantification of fundamental ion channel properties.

Anal Chim Acta

Bio-ID Center, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China. Electronic address:

Published: May 2020

One of the most widely used approaches to characterize transmembrane ion transport through nanoscale synthetic or biological channels is a straightforward, liposome-based assay that monitors changes in ionic flux across the vesicle membrane using pH- or ion-sensitive dyes. However, failure to account for the precise experimental conditions, in particular the complete ionic composition on either side of the membrane and the inherent permeability of ions through the lipid bilayer itself, can prevent quantifications and lead to fundamentally incorrect conclusions. Here we present a quantitative model for this assay based on the Goldman-Hodgkin-Katz flux theory, which enables accurate measurements and identification of optimal conditions for the determination of ion channel permeability and selectivity. Based on our model, the detection sensitivity of channel permeability is improved by two orders of magnitude over the commonly used experimental conditions. Further, rather than obtaining qualitative preferences of ion selectivity as is typical, we determine quantitative values of these parameters under rigorously controlled conditions even when the experimental results would otherwise imply (without our model) incorrect behavior. We anticipate that this simply employed ultrasensitive assay will find wide application in the quantitative characterization of synthetic or biological ion channels.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.aca.2020.03.044DOI Listing

Publication Analysis

Top Keywords

liposome-based assay
8
ion channel
8
synthetic biological
8
experimental conditions
8
channel permeability
8
ion
5
ultrasensitive liposome-based
4
assay
4
assay quantification
4
quantification fundamental
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!