Sengupta Nilapratim, Manchanda Rohit
Department of Biosciences and Bioengineering, Indian Institute of Technology Bombay, Mumbai, 400076, India.
J Comput Neurosci. 2019 Dec;47(2-3):167-189. doi: 10.1007/s10827-019-00731-7. Epub 2019 Nov 12.
The detrusor, a key component of the urinary bladder wall, is a densely innervated syncytial smooth muscle tissue. Random spontaneous release of neurotransmitter at neuromuscular junctions (NMJs) in the detrusor gives rise to spontaneous excitatory junction potentials (SEJPs). These sub-threshold passive signals not only offer insights into the syncytial nature of the tissue, their spatio-temporal integration is critical to the generation of spontaneous neurogenic action potentials which lead to focal contractions during the filling phase of the bladder. Given the structural complexity and the contractile nature of the tissue, electrophysiological investigations on spatio-temporal integration of SEJPs in the detrusor are technically challenging. Here we report a biophysically constrained computational model of a detrusor syncytium overlaid with spatially distributed innervation, using which we explored salient features of the integration of SEJPs in the tissue and the key factors that contribute to this integration. We validated our model against experimental data, ascertaining that observations were congruent with theoretical predictions. With the help of comparative studies, we propose that the amplitude of the spatio-temporally integrated SEJP is most sensitive to the inter-cellular coupling strength in the detrusor, while frequency of observed events depends more strongly on innervation density. An experimentally testable prediction arising from our study is that spontaneous release frequency of neurotransmitter may be implicated in the generation of detrusor overactivity. Set against histological observations, we also conjecture possible changes in the electrical activity of the detrusor during pathology involving patchy denervation. Our model thus provides a physiologically realistic, heuristic framework to investigate the spread and integration of passive potentials in an innervated syncytial tissue under normal conditions and in pathophysiology.
逼尿肌是膀胱壁的关键组成部分,是一种神经支配密集的合胞体平滑肌组织。逼尿肌神经肌肉接头(NMJ)处神经递质的随机自发释放会引发自发兴奋性接头电位(SEJP)。这些阈下被动信号不仅有助于深入了解组织的合胞体性质,其时空整合对于自发神经源性动作电位的产生至关重要,而这种动作电位会在膀胱充盈期导致局部收缩。鉴于该组织的结构复杂性和收缩性质,对逼尿肌中SEJP时空整合进行电生理研究在技术上具有挑战性。在此,我们报告了一个具有空间分布神经支配的逼尿肌合胞体的生物物理约束计算模型,利用该模型我们探索了组织中SEJP整合的显著特征以及促成这种整合的关键因素。我们根据实验数据验证了我们的模型,确定观察结果与理论预测一致。通过比较研究,我们提出时空整合的SEJP的幅度对逼尿肌中的细胞间耦合强度最为敏感,而观察到的事件频率则更强烈地依赖于神经支配密度。我们的研究得出的一个可通过实验验证的预测是,神经递质的自发释放频率可能与逼尿肌过度活动的产生有关。对照组织学观察结果,我们还推测了在涉及局部去神经支配的病理过程中逼尿肌电活动可能发生的变化。因此,我们的模型提供了一个生理现实的启发式框架,用于研究正常条件下和病理生理学中神经支配合胞体组织中被动电位的传播和整合。