Tegtmeyer Matthew, Liyanage Dhara, Han Yu, Hebert Kathryn B, Pei Ruifan, Way Gregory P, Ryder Pearl V, Hawes Derek, Tromans-Coia Callum, Cimini Beth A, Carpenter Anne E, Singh Shantanu, Nehme Ralda
bioRxiv. 2024 Nov 17:2024.11.16.623947. doi: 10.1101/2024.11.16.623947.
Neuropsychiatric conditions pose substantial challenges for therapeutic development due to their complex and poorly understood underlying mechanisms. High-throughput, unbiased phenotypic assays present a promising path for advancing therapeutic discovery, especially within disease-relevant neural tissues. Here, we introduce NeuroPainting, a novel adaptation of the Cell Painting assay, optimized for high-dimensional morphological phenotyping of neural cell types, including neurons, neuronal progenitor cells, and astrocytes derived from human stem cells. Using NeuroPainting, we quantified cell structure and organelle behavior across various brain cell types, creating a public dataset of over 4,000 cellular traits. This extensive dataset not only sets a new benchmark for phenotypic screening in neuropsychiatric research but also serves as a gold standard for the research community, enabling comparisons and validation of results. We then applied NeuroPainting to identify morphological signatures associated with the 22q11.2 deletion, a major genetic risk factor for schizophrenia. We observed profound cell-type-specific effects of the 22q11.2 deletion, with significant alterations in mitochondrial structure, endoplasmic reticulum organization, and cytoskeletal dynamics, particularly in astrocytes. Transcriptomic analysis revealed reduced expression of cell adhesion genes in 22q11.2 deletion astrocytes, consistent with recent post-mortem findings. Integrating the RNA sequencing data and morphological profiles uncovered a novel biological link between altered expression of specific cell adhesion molecules and observed changes in mitochondrial morphology in 22q11.2 deletion astrocytes. These findings underscore the power of combined phenomic and transcriptomic analyses to reveal mechanistic insights associated with human genetic variants of neuropsychiatric conditions.
神经精神疾病因其复杂且鲜为人知的潜在机制,给治疗开发带来了巨大挑战。高通量、无偏倚的表型分析为推进治疗发现提供了一条有前景的途径,尤其是在与疾病相关的神经组织中。在此,我们介绍NeuroPainting,这是一种对细胞绘画分析的新颖改编,针对神经细胞类型(包括源自人类干细胞的神经元、神经祖细胞和星形胶质细胞)的高维形态表型分析进行了优化。使用NeuroPainting,我们量化了各种脑细胞类型中的细胞结构和细胞器行为,创建了一个包含超过4000个细胞特征的公共数据集。这个广泛的数据集不仅为神经精神疾病研究中的表型筛选设定了新的基准,也为研究界提供了一个金标准,能够对结果进行比较和验证。然后,我们应用NeuroPainting来识别与22q11.2缺失相关的形态特征,22q11.2缺失是精神分裂症的一个主要遗传风险因素。我们观察到2