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在单通道水平上对缝隙连接通道电压门控的建模与分析。

Modeling and analysis of voltage gating of gap junction channels at a single-channel level.

机构信息

Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania; Department of Mathematical Modelling, Kaunas University of Technology, Kaunas, Lithuania.

Institute of Cardiology, Lithuanian University of Health Sciences, Kaunas, Lithuania.

出版信息

Biophys J. 2023 Nov 7;122(21):4176-4193. doi: 10.1016/j.bpj.2023.09.015. Epub 2023 Sep 27.

Abstract

The advancement of single-channel-level recording via the patch-clamp technique has provided a powerful means of assessing the detailed behaviors of various types of ion channels in native and exogenously expressed cellular environments. However, such recordings of gap junction (GJ) channels are hampered by unique challenges that are related to their unusual intercellular configuration and natural clustering into densely packed plaques. Thus, the methods for reliable cross-correlation of data recorded at macroscopic and single-channel levels are lacking in studies of GJs. To address this issue, we combined our previously published four-state model (4SM) of GJ channel gating by voltage with maximum likelihood estimation (MLE)-based analyses of electrophysiological recordings of GJ channel currents. First, we consider evaluation of single-channel characteristics and the methods for efficient stochastic simulation of single GJ channels from the kinetic scheme described by 4SM using data obtained from macroscopic recordings. We then present an MLE-based methodology for extraction of information about transition rates for GJ channels and, ultimately, gating parameters defined in 4SM from recordings with visible unitary events. The validity of the proposed methodology is illustrated using stochastic simulations of single GJ channels and is extended to electrophysiological data recorded in cells expressing connexin 43 tagged with enhanced green fluorescent protein.

摘要

通过膜片钳技术的单通道水平记录的进步为评估各种类型的离子通道在天然和外源性表达的细胞环境中的详细行为提供了一种强大的手段。然而,缝隙连接 (GJ) 通道的这种记录受到独特挑战的阻碍,这些挑战与它们不寻常的细胞间结构和自然聚集到密集斑块有关。因此,在 GJ 的研究中,缺乏在宏观和单通道水平上可靠地对数据进行互相关的方法。为了解决这个问题,我们结合了我们之前发表的电压门控 GJ 通道四态模型 (4SM) 和基于最大似然估计 (MLE) 的 GJ 通道电流电生理记录分析。首先,我们考虑从 4SM 描述的动力学方案中评估单通道特性和从宏观记录中获得的数据对单个 GJ 通道进行有效随机模拟的方法。然后,我们提出了一种基于 MLE 的方法,用于从具有可见单位事件的记录中提取关于 GJ 通道的跃迁率和最终定义在 4SM 中的门控参数的信息。使用单个 GJ 通道的随机模拟验证了所提出方法的有效性,并将其扩展到表达增强型绿色荧光蛋白标记的连接蛋白 43 的细胞中记录的电生理数据。

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