Division of Biological Sciences, University of California San Diego, La Jolla, California, United States of America.
Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, California, United States of America.
PLoS Comput Biol. 2022 May 9;18(5):e1010068. doi: 10.1371/journal.pcbi.1010068. eCollection 2022 May.
Chemical synapses exhibit a diverse array of internal mechanisms that affect the dynamics of transmission efficacy. Many of these processes, such as release of neurotransmitter and vesicle recycling, depend strongly on activity-dependent influx and accumulation of Ca2+. To model how each of these processes may affect the processing of information in neural circuits, and how their dysfunction may lead to disease states, requires a computationally efficient modelling framework, capable of generating accurate phenomenology without incurring a heavy computational cost per synapse. Constructing a phenomenologically realistic model requires the precise characterization of the timing and probability of neurotransmitter release. Difficulties arise in that functional forms of instantaneous release rate can be difficult to extract from noisy data without running many thousands of trials, and in biophysical synapses, facilitation of per-vesicle release probability is confounded by depletion. To overcome this, we obtained traces of free Ca2+ concentration in response to various action potential stimulus trains from a molecular MCell model of a hippocampal Schaffer collateral axon. Ca2+ sensors were placed at varying distance from a voltage-dependent calcium channel (VDCC) cluster, and Ca2+ was buffered by calbindin. Then, using the calcium traces to drive deterministic state vector models of synaptotagmin 1 and 7 (Syt-1/7), which respectively mediate synchronous and asynchronous release in excitatory hippocampal synapses, we obtained high-resolution profiles of instantaneous release rate, to which we applied functional fits. Synchronous vesicle release occurred predominantly within half a micron of the source of spike-evoked Ca2+ influx, while asynchronous release occurred more consistently at all distances. Both fast and slow mechanisms exhibited multi-exponential release rate curves, whose magnitudes decayed exponentially with distance from the Ca2+ source. Profile parameters facilitate on different time scales according to a single, general facilitation function. These functional descriptions lay the groundwork for efficient mesoscale modelling of vesicular release dynamics.
化学突触表现出多种多样的内部机制,这些机制会影响传递效率的动态。其中许多过程,如神经递质的释放和囊泡的再循环,强烈依赖于活性依赖的 Ca2+内流和积累。为了模拟这些过程中的每一个过程如何影响神经回路中的信息处理,以及它们的功能障碍如何导致疾病状态,需要一个计算效率高的建模框架,能够在不增加每个突触的计算成本的情况下产生准确的现象。构建一个现象学上逼真的模型需要精确地描述神经递质释放的时间和概率。困难在于,没有运行数千次试验,就很难从嘈杂的数据中提取出瞬时释放率的函数形式,并且在生物物理突触中,囊泡释放概率的易化受到耗竭的影响。为了克服这个问题,我们从海马 CA1 树突棘的分子 MCell 模型中获得了对各种动作电位刺激序列的游离 Ca2+浓度的轨迹。Ca2+传感器放置在距电压依赖性钙通道 (VDCC) 簇的不同距离处,并用钙结合蛋白进行 Ca2+缓冲。然后,我们使用钙轨迹来驱动突触融合蛋白 1 和 7 (Syt-1/7) 的确定性状态向量模型,这两种蛋白分别介导兴奋性海马突触中的同步和异步释放,从而获得瞬时释放率的高分辨率轮廓,我们对其进行了功能拟合。同步囊泡释放主要发生在 Spike 诱发的 Ca2+内流源的半微米范围内,而异步释放则在所有距离上更一致地发生。快速和慢速机制都表现出多指数释放率曲线,其幅度随与 Ca2+源的距离呈指数衰减。根据单个通用易化函数,轮廓参数根据不同的时间尺度进行调节。这些功能描述为囊泡释放动力学的高效介观建模奠定了基础。