MONTE CARLO SIMULATION OF PRESYNAPTIC CALCIUM DYNAMICS AND NEUROTRANSMITTER REL

突触前钙动力学和神经递质相关性的蒙特卡罗模拟

• 批准号: 8364252
• 负责人: JOEL R. STILES
• 金额: $ 8.65万
• 依托单位: CARNEGIE-MELLON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-15 至 2013-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8364252
• 关键词: 3-Dimensional; Action Potentials; Algorithms; Architecture; Binding; Binding Sites; Biomedical Research; Calcium; Calcium Binding; Calcium Channel; Calcium Signaling; Calcium ion; Coupled; Data; Diffusion; Dimensions; Experimental Models; Funding; Generations; Grant; High Performance Computing; Ions; Kinetics; Length; Lipid Binding; Manuscripts; Membrane Lipids; Memory; Modeling; National Center for Research Resources; Nerve; Neurotransmitters; Operating System; Output; Pattern; Physiological; Postdoctoral Fellow; Preparation; Principal Investigator; Probability; Process; Proteins; Publications; Publishing; Rana; Research; Research Infrastructure; Resources; Running; SNAP receptor; Simulate; Site; Source; Speed; Structure; Synaptic Vesicles; System; Time; United States National Institutes of Health; Vesicle; Work; abstracting; base; cost; design; extracellular; mathematical model; nanosecond; neuromuscular; neurotransmitter release; presynaptic; sensor; shared memory; simulation; stoichiometry; synaptotagmin I; voltage

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Monte Carlo simulation of presynaptic calcium dynamics and neurotransmitter release. This computational project is directed by J. Stiles and is being carried out by John Pattillo, a post-doc in his lab. Using realistic nerve terminal ultrastructure and data such as that described in II.A.1.c, MCell simulations of active zone calcium dynamics encompass action potential-activation of voltage-gated calcium channels, stochastic calcium ion entry and diffusion, calcium binding to sensor sites on arrays of synaptic vesicles, and prediction of vesicle fusion and resulting transmitter release. To our knowledge, this is the only study to date that has included the 3-D structure of an entire presynaptic active zone, and that has used multiple experimental constraints to enable quantitative predictions, e.g., the number of calcium-binding sites on synaptic vesicles, and the relationship between number of binding sites, number of sites that must be bound to initiate neurotransmitter release, and the importance of active zone spatial organization. In brief, a supralinear (~4th order)1 relationship (CRR) between extracellular Ca2+ ([Ca2+]o) and transmitter release indicates that multiple Ca2+ ions are required for fusion of a synaptic vesicle (SV), but how this empirical observation relates to the stoichiometry and architecture of voltage-gated Ca2+ channels (VGCCs), Ca2+ binding sites, and SVs is unclear. We created a spatially realistic model of a frog neuromuscular active zone (AZ), and used MCell to simulate action potential (AP)-induced Ca2+ influx through VGCCs, Ca2+ binding to SVs, and several models of Ca2+-dependent SV fusion. We varied spatial parameters to simultaneously reproduce 3 experimental observations: 1.) average release probability (pr) per trial per AZ at physiological [Ca2+]o; 2.) the distribution of release latencies (Ldis); and 3.) the 4th order CRR. Also, a 4-state VGCC model reproduced macroscopic Ca2+ current kinetics, and the on and off rates for Ca2+ binding were based on the synaptotagmin-1 C2A domain. Given all these constraints, we obtained a surprisingly unique set of model parameters and several counter-intuitive predictions. With a VGCC:SV stoichiometry of 1:1 (supported by the experimental and mathematical modeling data outlined above), each SV contains ~20 Ca2+ binding sites, and 6 sites must be bound simultaneously to induce fusion. Alternative models were either much too Ca2+-insensitive to reproduce pr or could not simultaneously reproduce Ldis and CRR. These results demonstrate the dramatic sensitivity of CRR, pr, and Ldis to presynaptic architecture, and suggest that vesicle fusion may require a variety of SNARE protein and membrane lipid binding sites for Ca2+. This work has been published in abstract form (Pattillo et al., 2004), and several full length manuscripts are in preparation. This project has required something on the scale of 105 simulations to date, primarily run on the PSC HP GS1280 machine(s), for which we are one of the preferred user groups. This machine is based on latest-generation Alpha EV7 processors, large shared memory, and outstanding memory bandwidth, and is optimally suited to our Monte Carlo algorithms and run-time optimizations within MCell. Specifically, MCell simulations require larges amounts of memory with random access patterns. In addition, this project admirably demonstrates the advantages to MCell's unique Monte Carlo algorithms for bimolecular interactions. The spatial dimensions of the active zone are tightly confined, and our simulations show that the average calcium concentration in the vicinity of vesicular binding sites corresponds to less than a single ion at any instant in time. Despite these conditions, MCell is able to accurately simulate these calcium dynamics with a time step on the sub-microsecond scale, rather than the sub-nanosecond scale (as would be required with less sophisticated algorithms for bimolecular interactions). Thus, this project has been possible only through a combination of optimized algorithms coupled with outstandingly designed and supported hardware. Computational Challenges These simulation have been performed using PSC's Marvel systems. Within this study, we are usually running one "project" at any given time. Each "project" includes 24 "sets" of simulations, and each "set" requires 500-1000 separate (embarrassingly parallel) simulations, each of which runs in 3 GBytes of RAM. Because of the Marvel's outstanding memory bandwidth and MCell's frequent random memory accesses, our simulations run very efficiently even compared to other more recent processors running at higher clock speeds. Perhaps even more important, we have never had any problems related to compilers or operating system issues. This is especially impressive given that each "project" generates up to 48 million output files that would consume up to 2.4 TBytes of disk space, except that we post-process the results on-the-fly, obtaining a reduction of ~1000-fold before transfer to mass storage. Without a stable system combining large memory, outstanding memory bandwidth, fast I/O, and reliable transfer to mass storage, our projects probably could not have been done. Publications: Pattillo, JM, Meriney, SD, and Stiles, JR., 2004, in press, Spatially realistic Monte Carlo simulations predict calcium dynamics underlying transmitter release at a neuromuscular active zone. Soc. Neurosci. Abst. Footnotes: 1. The calcium source is generally more than one channel, each of which is at a different distance from the vesicle that happens to fuse. The calcium sensing (binding) sites are arrayed around the base of each vesicle. The calcium gradient is very steep and different (in space and time) from each channel to each sensor. Thus it is very different from a situation in which multiple binding sites are each responding to the same calcium signal. The apparent cooperativity also depends on how we define the fusion model, e.g., the results are different depending on whether or not we require ~6 sites to be bound simultaneously or just to have been bound at some point in time.

该子项目是利用 NIH/NCRR 资助的中心拨款提供的资源的众多研究子项目之一。对子项目和子项目主要研究者的主要支持可能是由其他来源提供的，包括其他 NIH 来源。 子项目列出的总成本可能代表子项目使用的中心基础设施的估计金额，而不是 NCRR 拨款向子项目或子项目工作人员提供的直接资金。突触前钙动力学和神经递质释放的蒙特卡罗模拟。 该计算项目由 J. Stiles 指导，由其实验室的博士后 John Pattillo 负责实施。 使用真实的神经末梢超微结构和数据（如 II.A.1.c 中所述），MCell 模拟活动区钙动力学包括电压门控钙通道的动作电位激活、随机钙离子进入和扩散、钙与传感器的结合突触囊泡阵列上的位点，并预测囊泡融合和由此产生的递质释放。 据我们所知，这是迄今为止唯一一项包含整个突触前活动区的 3-D 结构的研究，并且使用多个实验约束来实现定量预测，例如突触小泡上钙结合位点的数量，以及结合位点数量、必须结合以启动神经递质释放的位点数量以及活动区空间组织的重要性之间的关系。 简而言之，细胞外 Ca2+ ([Ca2+]o) 和递质释放之间的超线性（~4 阶）1 关系 (CRR) 表明突触小泡 (SV) 的融合需要多个 Ca2+ 离子，但这一经验观察结果如何关联电压门控 Ca2+ 通道 (VGCC)、Ca2+ 结合位点和 SV 的化学计量和结构尚不清楚。 我们创建了青蛙神经肌肉活动区 (AZ) 的空间真实模型，并使用 MCell 模拟动作电位 (AP) 诱导的 Ca2+ 通过 VGCC 流入、Ca2+ 与 SV 结合以及 Ca2+ 依赖的 SV 融合的几种模型。 我们改变空间参数以同时重现 3 个实验观察结果： 1.) 在生理 [Ca2+]o 下每个 AZ 每次试验的平均释放概率 (pr)； 2.) 发布延迟的分布（Ldis）；和 3.) 第 4 阶 CRR。 此外，4 态 VGCC 模型再现了宏观 Ca2+ 电流动力学，Ca2+ 结合的开启和关闭速率基于 synaptotagmin-1 C2A 结构域。 考虑到所有这些限制，我们获得了一组令人惊讶的独特模型参数和一些反直觉的预测。 VGCC:SV 化学计量为 1:1（由上述实验和数学模型数据支持），每个 SV 包含约 20 个 Ca2+ 结合位点，并且必须同时结合 6 个位点才能诱导融合。 替代模型要么对 Ca2+ 太不敏感而无法复制 pr，要么无法同时复制 Ldis 和 CRR。 这些结果证明了 CRR、pr 和 Ldis 对突触前结构的高度敏感性，并表明囊泡融合可能需要多种 SNARE 蛋白和 Ca2+ 的膜脂结合位点。 这项工作已以摘要形式出版（Pattillo et al., 2004），几份完整的手稿正在准备中。 迄今为止，该项目需要进行 105 次模拟，主要在 PSC HP GS1280 机器上运行，我们是该机器的首选用户组之一。 该机器基于最新一代 Alpha EV7 处理器、大容量共享内存和出色的内存带宽，最适合我们的蒙特卡洛算法和 MCell 内的运行时优化。具体来说，MCell 模拟需要大量具有随机访问模式的内存。此外，该项目出色地展示了 MCell 独特的蒙特卡罗算法在双分子相互作用方面的优势。 活性区的空间尺寸受到严格限制，我们的模拟表明，囊泡结合位点附近的平均钙浓度在任何时刻对应的离子都少于单个离子。 尽管存在这些条件，MCell 仍能够以亚微秒尺度的时间步长（而不是亚纳秒尺度）（如不太复杂的双分子相互作用算法所需的时间步长）准确模拟这些钙动力学。 因此，这个项目只有通过优化算法的结合以及出色的 设计并支持硬件。 计算挑战 这些模拟是使用 PSC 的 Marvel 系统进行的。在这项研究中，我们通常在任何给定时间运行一个“项目”。 每个“项目”包括 24 个“组”模拟，每个“组”需要 500-1000 个单独的（令人尴尬的并行）模拟，每个模拟都在 3 GB RAM 中运行。 由于 Marvel 出色的内存带宽和 MCell 频繁的随机内存访问，即使与其他以更高时钟速度运行的最新处理器相比，我们的模拟运行也非常高效。 也许更重要的是，我们从未遇到过任何与编译器或操作系统相关的问题。 这是特别令人印象深刻的，因为每个“项目”生成多达 4800 万个输出文件，将消耗多达 2.4 TB 的磁盘空间，除非我们即时对结果进行后处理，从而减少了约 1000 倍在传输到大容量存储之前。 如果没有一个稳定的系统结合大内存、出色的内存带宽、快速 I/O 和可靠的海量存储传输，我们的项目可能无法完成。 出版物： Pattillo, JM、Meriney, SD 和 Stiles, JR.，2004 年，出版中，空间真实蒙特卡罗模拟预测神经肌肉活动区递质释放的钙动力学。 苏克。神经科学。摘要。 脚注： 1.钙源一般不止一个通道，每个通道与恰好融合的囊泡的距离不同。 钙传感（结合）位点排列在每个囊泡的底部周围。 每个通道到每个传感器的钙梯度非常陡峭且不同（在空间和时间上）。 因此，它与多个结合位点各自响应相同钙信号的情况非常不同。 明显的协同性还取决于我们如何定义融合模型，例如，结果会有所不同，具体取决于我们是否需要同时结合约 6 个位点或仅在某个时间点结合。