Department of Pathology, Stanford University, 300 Pasteur Dr., Stanford, CA, 94304, USA.
Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, Stanford, CA, USA.
Sci Rep. 2023 Aug 24;13(1):13849. doi: 10.1038/s41598-023-40683-8.
Comparing brain structure across species and regions enables key functional insights. Leveraging publicly available data from a novel mass cytometry-based method, synaptometry by time of flight (SynTOF), we applied an unsupervised machine learning approach to conduct a comparative study of presynapse molecular abundance across three species and three brain regions. We used neural networks and their attractive properties to model complex relationships among high dimensional data to develop a unified, unsupervised framework for comparing the profile of more than 4.5 million single presynapses among normal human, macaque, and mouse samples. An extensive validation showed the feasibility of performing cross-species comparison using SynTOF profiling. Integrative analysis of the abundance of 20 presynaptic proteins revealed near-complete separation between primates and mice involving synaptic pruning, cellular energy, lipid metabolism, and neurotransmission. In addition, our analysis revealed a strong overlap between the presynaptic composition of human and macaque in the cerebral cortex and neostriatum. Our unique approach illuminates species- and region-specific variation in presynapse molecular composition.
比较不同物种和区域的大脑结构可以提供关键的功能见解。利用基于新型飞行时间质谱细胞术（SynTOF）的公开可用数据，我们应用无监督机器学习方法，对三种物种和三个脑区的突触前分子丰度进行了比较研究。我们使用神经网络及其吸引人的特性来模拟高维数据之间的复杂关系，从而开发了一个统一的、无监督的框架，用于比较正常人类、猕猴和小鼠样本中超过 450 万个单个突触前体的分布。广泛的验证表明，使用 SynTOF 分析进行跨物种比较是可行的。对 20 种突触前蛋白丰度的综合分析表明，涉及突触修剪、细胞能量、脂质代谢和神经传递的灵长类动物和小鼠之间几乎完全分离。此外，我们的分析还揭示了人类和猕猴大脑皮层和新纹状体中突触前组成的强烈重叠。我们独特的方法阐明了突触前分子组成的物种和区域特异性变化。
