Deciphering the building blocks of the macaque prefrontal cortical microcircuit

摘要 自拉蒙·伊·卡哈尔以来，神经学家一直推测，即使是最复杂的大脑功能也可能- 实际上是在神经细胞类型及其连接的水平上理解的。最近，虽然我们已经- 为了了解啮齿动物大脑皮层微电路的连线原理，在细胞类型的水平上，我们还处于 婴儿期在细胞类型和细胞水平上理解灵长类新皮质的回路组织 连接，减缓了对复杂认知能力的机械性理解的进程- 灵长类动物的特征。例如，灵长类大脑的背外侧前额叶皮质(DLPFC)是 进化发展的大脑区域，支持灵长类动物特有的复杂认知过程， 比如推理、计划和抽象思维。然而，我们对构成细胞的类型知之甚少。 包括DLPFC电路，每种单元类型如何连接形成一个功能电路，以及什么电路 该电路特有的组件使其具有出色的复杂认知过程的计算能力。 赛斯。为了填补这一知识空白，我们扩大了一种具有成本效益的跨学科方法来研究猕猴 DLPFC，旨在识别其所有组成的信元类型并破译它们的连通性规则，重点是 在高度多样化的GABA能中间神经元上。我们建议使用多细胞贴片记录，单细胞RNA 测序(scRNA-seq)、新颖快速的病毒GABA能标记和机器学习实现了两个主要 目标：1)通过建立DLPFC细胞类型的形态分类学，剖析猕猴DLPFC微电路 以及2)获得形态上定义的DLPFC的转录签名 神经元使用Patch-seq方法，一种新的scRNA-seq协议。我们已经证明了这一点的可行性和成功-- 我们的初步数据表明，这种方法在小鼠新皮质中的应用没有技术问题 接近灵长类动物。使用多细胞斑片记录，我们将表征电生理学和形态 以及来自DLPFC的数万个细胞对之间的连接。vbl.使用 Patch-seq方法，我们将把补丁记录与一种新颖/敏感的scRNA-seq方法(Smart-seq2)相结合，以 同时获得单个神经元的电生理、形态和转录组，从而可以进一步 充实细胞类型分类，并为每种细胞类型确定新的分子标记。我们将确定优先顺序 我们对DLPFC表层的努力，但如果时间允许，最终会将我们的努力扩大到所有层。在 最终，该项目将揭示猕猴DLPFC的高分辨率微电路蓝图，每个电路组件- Ponent由特定的遗传标记识别。这样一个全面的数据集将提供基本的基础- 为进一步剖析复杂的认知过程设计分子工具的工作 被一等兵。从临床角度来看，具有不同细胞的参考转录本和连接模式 灵长类DLPFC的类型将有助于我们理解疾病相关基因之间的关系， 神经精神疾病，特别是精神分裂症的细胞类型和电路缺陷。

Abstract Since Ramon y Cajal, neuroscientists have speculated that even the most complex brain functions might even- tually be understood at the level of neuronal cell types and their connections. More recently, while we have be- gun to understand the wiring principles of cortical microcircuit in rodents at the level of cell types, we are still in infancy in understanding the circuit organization of the primate neocortex at the level of cell types and their connections, slowing the progress toward a mechanistic understanding of complex cognitive capabilities char- acteristic of primates. For instance, the dorsolateral prefrontal cortex (DLPFC) of the primate brain is the most evolutionarily developed brain region that supports complex cognitive processes characteristic of primates, such as reasoning, planning, and abstract thinking. However, we know little about the constituent cell types comprising DLPFC circuit, how each cell type connects each other to form a functional circuit, and what circuit components specific to this circuit endow it with superb computational capabilities for complex cognitive pro- cesses. To fill in this knowledge gap, we scale up a cost-effective, interdisciplinary approach to macaque DLPFC, aiming at identifying all its consitiuent cell types and decipher their connectivity rules, with emphasis on highly diverse GABAergic interneurons. We propose to use multi-cell patch recordings, single-cell RNA sequencing (scRNA-seq), novel and rapid viral GABAergic labeling, and machine learning to achieve two main goals: 1) dissect macaque DLPFC microcircuit by generating a morphological taxonomy of cell types in DLPFC and mapping their connections; and 2) derive transcriptomic signatures of morphologically defined DLPFC neurons using Patch-seq method, a novel scRNA-seq protocol. We have demonstrated the feasibility and suc- cess of this approach in mouse neocortex, and our preliminary data indicate no technical issue in applying this approach to primates. Using multi-cell patch recordings, we will characterize electrophysiology and morphology of thousands of neurons and map connections between tens of thousands of cell pairs from DLPFC. Using Patch-seq method, we will combine patch recording with a novel/sensitive scRNA-seq method (Smart-seq2) to simultaneously obtain electrophysiology, morphology and transcriptome from single neurons, which can further substantiate cell type classification and identify novel molecular markers for each cell type. We will prioritize our effort on superficial layers of DLPFC, but eventually scale up our efforts to all layers if time permits. At the end, the project will uncover a high-resolution microcircuit blueprint of macaque DLPFC with each circuit com- ponent identified by specific genetic markers. Such a comprehensive dataset will provide the essential ground- work to design molecular tools for further functional dissection of the complex cognitive processes subserved by PFC. From a clinical perspective, having reference transcriptomes and connectivity patterns for different cell types in primate DLPFC will facilitate our understanding of the relationship between disease-associated genes, cell types, and circuit deficits in neuropsychiatric diseases, schizophrenia in particular.