Yan Jiajie, Thomson Justin K, Wu Xiaomin, Zhao Weiwei, Pollard Andrew E, Ai Xun
Department of Cell and Molecular Physiology, Loyola University Chicago, Maywood, Illinois, United States of America.
Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, Alabama, United States of America.
PLoS One. 2014 Aug 8;9(8):e104357. doi: 10.1371/journal.pone.0104357. eCollection 2014.
Gap junctions (GJs) are the principal membrane structures that conduct electrical impulses between cardiac myocytes while interstitial collagen (IC) can physically separate adjacent myocytes and limit cell-cell communication. Emerging evidence suggests that both GJ and interstitial structural remodeling are linked to cardiac arrhythmia development. However, automated quantitative identification of GJ distribution and IC deposition from microscopic histological images has proven to be challenging. Such quantification is required to improve the understanding of functional consequences of GJ and structural remodeling in cardiac electrophysiology studies.
Separate approaches were employed for GJ and IC identification in images from histologically stained tissue sections obtained from rabbit and human atria. For GJ identification, we recognized N-Cadherin (N-Cad) as part of the gap junction connexin 43 (Cx43) molecular complex. Because N-Cad anchors Cx43 on intercalated discs (ID) to form functional GJ channels on cell membranes, we computationally dilated N-Cad pixels to create N-Cad units that covered all ID-associated Cx43 pixels on Cx43/N-Cad double immunostained confocal images. This approach allowed segmentation between ID-associated and non-ID-associated Cx43. Additionally, use of N-Cad as a unique internal reference with Z-stack layer-by-layer confocal images potentially limits sample processing related artifacts in Cx43 quantification. For IC quantification, color map thresholding of Masson's Trichrome blue stained sections allowed straightforward and automated segmentation of collagen from non-collagen pixels. Our results strongly demonstrate that the two novel image-processing approaches can minimize potential overestimation or underestimation of gap junction and structural remodeling in healthy and pathological hearts. The results of using the two novel methods will significantly improve our understanding of the molecular and structural remodeling associated functional changes in cardiac arrhythmia development in aged and diseased hearts.
缝隙连接(GJs)是在心肌细胞之间传导电冲动的主要膜结构,而间质胶原(IC)可在物理上分隔相邻的心肌细胞并限制细胞间通讯。新出现的证据表明,缝隙连接和间质结构重塑均与心律失常的发生有关。然而,从微观组织学图像中自动定量识别缝隙连接分布和间质胶原沉积已被证明具有挑战性。在心脏电生理研究中,需要进行这种量化以增进对缝隙连接和结构重塑功能后果的理解。
采用不同方法对从兔和人的心房获取的组织学染色切片图像中的缝隙连接和间质胶原进行识别。对于缝隙连接的识别,我们将N-钙黏蛋白(N-Cad)识别为缝隙连接蛋白43(Cx43)分子复合物的一部分。由于N-钙黏蛋白将Cx43锚定在闰盘(ID)上,从而在细胞膜上形成功能性缝隙连接通道,我们通过计算扩张N-钙黏蛋白像素以创建覆盖Cx43/N-钙黏蛋白双重免疫染色共聚焦图像上所有与闰盘相关的Cx43像素的N-钙黏蛋白单元。这种方法允许区分与闰盘相关和与闰盘无关的Cx43。此外,将N-钙黏蛋白用作具有Z轴逐层共聚焦图像的独特内部参考,可能会限制Cx43定量中与样品处理相关产生的伪影。对于间质胶原的定量,对Masson三色蓝染色切片进行彩色图阈值处理可直接自动地从非胶原像素中分割出胶原。我们的结果有力地证明,这两种新的图像处理方法可最大限度减少在健康和病理心脏中对缝隙连接和结构重塑的潜在高估或低估。使用这两种新方法的结果将显著增进我们对老年和患病心脏中心律失常发生过程中分子和结构重塑相关功能变化的理解。