1. Multiregional profiling of the brain transmembrane proteome uncovers novel regulators of depression
- Author
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Yaoyang Zhang, Cuiping Tian, Yan Liu, Ting Dang, Y. Li, Chengyu Fan, Zhuangzhuang Zhang, Hui Li, Shanshan Li, Fei Xu, Ronghui Lou, Huoqing Luo, Chen Pan, Lisha Xia, Pan Tang, Chen Miao, Wenqing Shui, Guisheng Zhong, Xiaoxiao Duan, and Ji Hu
- Subjects
0301 basic medicine ,Proteomics ,Proteome ,Computational biology ,Biology ,Neurotransmission ,environment and public health ,Biochemistry ,Receptors, G-Protein-Coupled ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Interaction network ,Profiling (information science) ,Animals ,Receptor ,Research Articles ,G protein-coupled receptor ,Messenger RNA ,Multidisciplinary ,Depression ,Brain ,SciAdv r-articles ,Transmembrane protein ,030104 developmental biology ,Cellular Neuroscience ,biological phenomena, cell phenomena, and immunity ,030217 neurology & neurosurgery ,hormones, hormone substitutes, and hormone antagonists ,Research Article - Abstract
In-depth profiling of transmembrane proteins in the brain leads to the identification of GPCR regulators in a disease model., Transmembrane proteins play vital roles in mediating synaptic transmission, plasticity, and homeostasis in the brain. However, these proteins, especially the G protein–coupled receptors (GPCRs), are underrepresented in most large-scale proteomic surveys. Here, we present a new proteomic approach aided by deep learning models for comprehensive profiling of transmembrane protein families in multiple mouse brain regions. Our multiregional proteome profiling highlights the considerable discrepancy between messenger RNA and protein distribution, especially for region-enriched GPCRs, and predicts an endogenous GPCR interaction network in the brain. Furthermore, our new approach reveals the transmembrane proteome remodeling landscape in the brain of a mouse depression model, which led to the identification of two previously unknown GPCR regulators of depressive-like behaviors. Our study provides an enabling technology and rich data resource to expand the understanding of transmembrane proteome organization and dynamics in the brain and accelerate the discovery of potential therapeutic targets for depression treatment.
- Published
- 2020