Computational Modeling of Channelrhodopsin-2 Photocurrent Characteristics in Relation to Neural Signaling

Abstract

Channelrhodopsins-2 (ChR2) are a class of light sensitive proteins that offer the ability to use light stimulation to regulate neural activity with millisecond precision. In order to address the limitations in the efficacy of the wild-type ChR2 (ChRwt) to achieve this objective, new variants of ChR2 that exhibit fast mon-exponential photocurrent decay characteristics have been recently developed and validated. In this paper, we investigate whether the framework of transition rate model with 4 states, primarily developed to mimic the biexponential photocurrent decay kinetics of ChRwt, as opposed to the low complexity 3 state model, is warranted to mimic the mono-exponential photocurrent decay kinetics of the newly developed fast ChR2 variants: ChETA (Gunaydin et al., Nature Neurosci. 13:387-392, 2010) and ChRET/TC (Berndt et al., Proc. Natl. Acad. Sci. 108:7595-7600, 2011). We begin by estimating the parameters of the 3-state and 4-state models from experimental data on the photocurrent kinetics of ChRwt, ChETA, and ChRET/TC. We then incorporate these models into a fast-spiking interneuron model (Wang and Buzsaki, J. Neurosci. 16:6402-6413, 1996) and a hippocampal pyramidal cell model (Golomb et al., J. Neurophysiol. 96:1912-1926, 2006) and investigate the extent to which the experimentally observed neural response to various optostimulation protocols can be captured by these models. We demonstrate that for all ChR2 variants investigated, the 4 state model implementation is better able to capture neural response consistent with experiments across wide range of optostimulation protocol. We conclude by analytically investigating the conditions under which the characteristic specific to the 3-state model, namely the monoexponential photocurrent decay of the newly developed variants of ChR2, can occur in the framework of the 4-state model.

Effects of Electrical and Optogenetic Deep Brain Stimulation on Synchronized Oscillatory Activity in Parkinsonian Basal Ganglia

“…We use a four-state transition rate model for the photocurrent kinetics following [21]. In particular, we use a model of ChETA, a ChR2 mutant with faster photocurrent dynamics.…”

“…The photocycle transitions of ChETA are represented via two sets of intra-transition states: closed states C 1 is the activation time of the ChETA ion channel (1.5855 ms). The function captures the temporal kinetics of the conformational change in protein [21]. The number of photons absorbed by ChETA molecule per unit time is given by F = σ ret φ/w loss , where σ ret is the retinal cross-section (1.2 x 10 -20 m 2 ) [22] and w loss is the loss of photons due to scattering and absorption.…”

“…Additionally, NpHR exhibits at least three states during light activation/inactivation [24] We estimated the parameters G d , G r , ε, and g NpHR by using experimental results [11,23] to construct an empirical curve that represents NpHR photocurrent dynamics. The empirical curve that fits the temporal profile of experimentally observed photocurrents can be estimated similar to [21] using:…”

Computational modeling of neurostimulation in brain diseases

“…In the second approach, the intrinsic channel dynamics of the opsin are specifically modeled to address questions regarding the detailed light-stimulation parameters required to achieve the desired change in membrane potential (Grossman et al, 2011). In terms of modeling, the detailed dynamics of the opsin, the main focus of attention has been the well-known channelrhodopsin (Foutz et al, 2012;Grossman et al, 2011;Nikolic et al, 2013;Stefanescu et al, 2013;. However, detailed models of other opsins (such as halorhodopsin, see Stefanescu et al, 2013) are in development.…”

“…In terms of modeling, the detailed dynamics of the opsin, the main focus of attention has been the well-known channelrhodopsin (Foutz et al, 2012;Grossman et al, 2011;Nikolic et al, 2013;Stefanescu et al, 2013;. However, detailed models of other opsins (such as halorhodopsin, see Stefanescu et al, 2013) are in development.…”