A platform for efficient identification of molecular phenotypes of brain-wide neural circuits. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Jiang, Tao; Long, Ben; Gong, Hui; Xu, Tonghui; Li, Xiangning; Duan, Zhuonan; Li, Anan; Deng, Lei; Zhong, Qiuyuan; Peng, Xue; Yuan, Jing
• Is Part Of: Scientific reports. Volume 7:Issue 1(2017)
• Page Start: 1
• Page End: 12
• Publication Date: 2017-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-017-14360-6
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract A neural circuit is a structural-functional unit of achieving particular information transmission and processing, and have various inputs, outputs and molecular phenotypes. Systematic acquisition and comparative analysis of the molecular features of neural circuits are crucial to elucidating the operating mechanisms of brain function. However, no efficient, systematic approach is available for describing the molecular phenotypes of specific neural circuits at the whole brain scale. In this study, we developed a rapid whole-brain optical tomography method and devised an efficient approach to map brain-wide structural and molecular information in the same brain: rapidly imaging and sectioning the whole brain as well as automatically collecting all slices; conveniently selecting slices of interest through quick data browsing and then performing post hoc immunostaining of selected slices. Using this platform, we mapped the brain-wide distribution of inputs to motor, sensory and visual cortices and determined their molecular phenotypes in several subcortical regions. Our platform significantly enhances the efficiency of molecular phenotyping of neural circuits and provides access to automation and industrialization of cell type analyses for specific circuits.