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

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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.