Multimodal profiling of neurons in 3D human cortical organoids using patch-seq

摘要 神经发育和神经-神经元通讯的缺陷会导致包括自闭症在内的精神障碍 谱系障碍和精神分裂症。精神分裂症的病理生理学研究进展 由于缺乏对分子、形态和功能的综合理解， 人类大脑中不同类型细胞的特性。虽然来自人类的3D皮质类器官诱导 多能干细胞（hiPSC）已用于模拟与病毒感染相关的神经病理学， 神经精神障碍，目前还不清楚是否可以忠实地早期大脑发育过程 由基于hiPSC的皮质类器官概括。对成千上万的细胞进行单细胞RNA测序， 人类皮质类器官提供了一个前所未有的机会来解剖空间和时间 以细胞类型特异性方式在早期神经元发育中的机制。这种方法使 基于转录组学特征，在几个物种和类器官中对许多神经类型进行分类， 与人类早期大脑发育中的细胞组成非常相似。尽管单方面取得了进展， 细胞转录组学，电生理特性以及不同类型的形态学特征， 大脑类器官中的人类神经元仍然难以捉摸。经典膜片钳的劳动密集型特性 电生理学和技术上的困难，记录从一个异质群体的神经元， 不同的成熟阶段限制了人类神经元功能数据的丰富性。因为 电生理表型由形态学特征贡献，由不同的膜离子控制 通道和受体，我们假设，电生理（和可能的形态学）的特点， 人类神经元可以通过单细胞转录组学谱来预测。这个探索性项目的主要目标 是建立一个基于电生理学、形态学和单细胞转录组学的细胞普查图， 在hiPSC-3D皮质类器官模型中的表达谱，并开发用于预测细胞凋亡的转录组学算法。 人类神经元的形态学-电生理学为实现这一目标，我们提出：1）建立小区普查 人类3D皮质类器官的神经亚型图，具有单细胞分辨率的功能注释; 2） 使用单细胞转录组学谱来预测细胞类型的形态和功能特性， 人类3D皮质类器官这个探索性的项目将使我们能够开发一个数据库， 具有细胞特性的转录组，包括电生理学和形态学特征， 基于转录组学数据预测大脑发育、健康和疾病中的神经元功能。这 这项研究具有巨大的潜力，使未来的研究，以确定神经元的功能特性， 基于转录组学数据的类器官，从而促进了健康早期大脑发育的建模， 疾病

Abstract Deficits in neurodevelopment and neuro-neuronal communications lead to mental disorders including autism spectrum disorder and schizophrenia in humans. The progress in understanding the pathophysiology of mental disorders is hampered by the lack of an integrative understanding of molecular, morphological and functional properties of diverse cell types in human brain. While 3D cortical organoids derived from human induced pluripotent stem cell (hiPSC) have been used to model neuropathology associated with virus infections and neuropsychiatric disorders, it is still unclear whether the early brain developmental process can be faithfully recapitulated by hiPSCs-based cortical organoids. Single-cell RNA sequencing of tens of thousands of cells of human cortical organoids has provided an unprecedented opportunity to dissect the spatial and temporal mechanism in early neuronal development in a cell type-specific manner. Such an approach has enabled the classification of many neural types in several species and organoids based on transcriptomic profiles, which are remarkably similar to the cellular compositions in human early brain development. Despite the advances in single cell transcriptomics, the electrophysiological properties as well as morphological features of different types of human neurons in brain organoids remain elusive. The labor-intensive nature of classical patch clamp electrophysiology and the technical difficulties in recording from a heterogeneous population of neurons at different stages of maturation had limited the abundance of functional data in human neurons. Because electrophysiological phenotypes, contributed by morphological features, are governed by distinct membrane ion channels and receptors, we hypothesize that electrophysiological (and possibly morphological) features of human neurons can be predicted by single cell transcriptomic profiles. The primary goal of this exploratory project is to establish a cell-census map based on electrophysiological, morphological and single cell transcriptomic profiles in a hiPSC-3D cortical organoid model and to develop a transcriptomic algorithm for predicting cell morphology-electrophysiology of human neurons. To achieve this goal, we propose: 1) to build a cell census map of neural subtypes of human 3D cortical organoids with functional annotation at single cell resolution; 2) to use using single cell transcriptomic profiles to predict the morphological and functional properties of cell types in human 3D cortical organoids. This exploratory project will allow us to develop a database to integrate single cell transcriptomes with cellular properties including electrophysiology and morphology profiles which enable predictions of neuronal functions in brain development, health and disease based on transcriptomic data. This study has enormous potential to enable future studies to ascertain the functional properties of neurons in organoids based on transcriptomic data, thus facilitating the modeling of early brain development in health and disease.