An optimized and automated approach to quantifying channelrhodopsin photocurrent kinetics

Channelrhodopsins are light-activated ion channels that enable targetable activation or inhibition of excitable cells with light. Ion conductance can generally be described by a four step photocycle, which includes two open and two closed states. While a complete understanding of channelrhodopsin fu...

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Vydané v:Analytical biochemistry Ročník 566; s. 160 - 167
Hlavní autori: Prignano, Lindsey, Faal, Siamak G., Hera, Adriana, Dempski, Robert E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: United States Elsevier Inc 01.02.2019
Predmet:
automation
Channelrhodopsin
electric current
Electrophysiology
ion channels
Kinetic modeling
Neuroscience
Optogenetics
quantitative analysis
Electrophysiology
Neuroscience
Optogenetics
Kinetic modeling
Channelrhodopsin
ISSN:0003-2697, 1096-0309, 1096-0309
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Shrnutí:Channelrhodopsins are light-activated ion channels that enable targetable activation or inhibition of excitable cells with light. Ion conductance can generally be described by a four step photocycle, which includes two open and two closed states. While a complete understanding of channelrhodopsin function cannot be understood in the absence of kinetic modeling, model fitting requires manual fitting, which is laborious and technically complicated for non-experts. To enhance analysis of photocurrent data, this manuscript describes a fitting program where electrophysiology data can be automatically and quantitatively analyzed. Significant improvement in this program when compared to our previous version includes 1) the ability to automatically find the experiment start time using the derivative of the current signal, 2) utilizing the Object Oriented Programing (OPP) paradigm which is significantly more reliable if the code is used by people with little to no programming experience and 3) the distribution of the code is simplified to sharing a single MATLAB file, including rigorous comments throughout. To demonstrate the utility of this program, we show automated fitting of photocurrents from two member proteins: channelrhodopsin-2 and a chimera between channelrhodopsin-1 and channelrhodopsin-2 (C1C2). •Channelrhodopsins have revolutionized neuroscience studies.•Channelrhodopsin has enabled spatial and temporal control over excitable cells.•Quantitative analysis of channelrhodopsin ion conductance is complicated.•We describe an automated program to provide quanitative channel conductance data.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0003-2697
1096-0309
1096-0309
DOI:10.1016/j.ab.2018.11.023