scholarly journals Correlated Single-Molecule Spectroscopy and Patch-Clamp Studies of Voltage Gated Ion Channel Activation Dynamics in Living Cells

2014 ◽  
Vol 106 (2) ◽  
pp. 746a
Author(s):  
Dibyendu Sasmal ◽  
H. Peter Lu
2020 ◽  
Author(s):  
Numan Celik ◽  
Sam T. M. Ball ◽  
Elaheh Sayari ◽  
Lina Abdul Kadir ◽  
Fiona O’Brien ◽  
...  

AbstractUnderstanding and accurately quantifying ion channel molecule gating in real time is vital for knowledge of cell membrane behaviour, drug discovery and toxicity screening. Doing this with single-molecule resolution first requires the detection of individual protein pore opening and closing transitions and construction of a so-called idealised record which indicates sample-point by samplepoint whether a given molecule is open or closed. Creating this can be difficult, since patch-clamp electrophysiology data can be noisy or contain multiple ion channel molecules. We have recently developed a deep learning model to achieve this called Deep-Channel, but further development is limited by the massive datasets need to train and validate models. In the past, this problem has been tackled by simulation of single molecule activity from Markov models with the addition of pseudo-random noise. In the present report we develop a new method to synthesise raw data, based on generative adversarial networks (GANs). The limitation to direct application of a GAN with this method has been that whilst there are methods to generate classified output image by image, there has been no method to generate an entire timeseries with parallel idealisation, sample-point by sample-point. In this paper, we over-come this problem with DeepGANnel, a model that splits training data raw and parallel idealised data into different rows of image windows and passes these data through a progressive-GAN. This new methodology allows generation of realistic, idealisation synchronised single molecule patch-clamp data, without the biases inherent in pseudorandom simulation methods. This method will be useful for development of single molecule analysis methods and may in the future prove useful for generation of biological models including single molecule resolution stochastic data. The model is easily extendable to other timeseries data requiring parallel labelling, such as labelled ECG.


2012 ◽  
Vol 29 (6) ◽  
pp. 275-282 ◽  
Author(s):  
SHU-JIE WANG ◽  
LAI-HUA XIE ◽  
BIN HENG ◽  
YAN-QIANG LIU

AbstractRetinal ganglion cell line (RGC-5) has been widely used as a valuable model for studying pathophysiology and physiology of retinal ganglion cells in vitro. However, the electrophysiological characteristics, especially a thorough classification of ionic currents in the cell line, remain to be elucidated in details. In the present study, we determined the resting membrane potential (RMP) in RGC-5 cell line and then identified different types of ionic currents by using the whole-cell patch-clamp technique. The RMP recorded in the cell line was between −30 and −6 mV (−17.6 ± 2.6 mV, n = 10). We observed the following voltage-gated ion channel currents: (1) inwardly rectifying Cl− current (ICl,ir), which could be blocked by Zn2+; (2) Ca2+-activated Cl− current (ICl,Ca), which was sensitive to extracellular Ca2+ and could be inhibited by disodium 4,4’-diisothiocyanatostilbene-2,2’-disulfonate; (3) inwardly rectifying K+ currents (IK1), which could be blocked by Ba2+; (4) a small amount of delayed rectifier K+ current (IK). On the other hand, the voltage-gated sodium channels current (INa) and transient outward potassium channels current (IA) were not observed in this cell line. These results further characterize the ionic currents in the RGC-5 cell line and are beneficial for future studies especially on ion channel (patho)physiology and pharmacology in the RGC-5 cell line.


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