小柯机器人

新技术助力感知编码机制的破译
2019-12-13 18:32

美国圣路易斯华盛顿大学医学院Timothy E. Holy研究团队通过生理定义神经元类型的光学标记技术,揭示了的感知编码机制。这一研究成果于2019年12月13日发表在国际学术期刊《科学》上。

研究人员开发了生理光学标记测序(PhOTseq),这是一种基于细胞功能特性进行标记和表达谱分析的技术。 PhOTseq能够选择稀有细胞类型并将其富集近100倍。研究人员将PhOTseq应用于在小鼠中信息素敏感神经元之间映射受体-配体配对的难题。结合犁鼻器化学受体的体内异位表达,PhOTseq鉴定了一组特定配体的完整组合受体密码。

据介绍,神经回路分析依赖于具有针对特定细胞类型的分子标记。然而,对于仅通过其回路功能识别的细胞类型,鉴定标记的过程仍然很费力。

附:英文原文

Title: Sensory coding mechanisms revealed by optical tagging of physiologically defined neuronal types

Author: Donghoon Lee, Maiko Kume, Timothy E. Holy

Issue&Volume: 2019/12/13

Abstract: Neural circuit analysis relies on having molecular markers for specific cell types. However, for a cell type identified only by its circuit function, the process of identifying markers remains laborious. We developed physiological optical tagging sequencing (PhOTseq), a technique for tagging and expression profiling of cells on the basis of their functional properties. PhOTseq was capable of selecting rare cell types and enriching them by nearly 100-fold. We applied PhOTseq to the challenge of mapping receptor-ligand pairings among pheromone-sensing neurons in mice. Together with in vivo ectopic expression of vomeronasal chemoreceptors, PhOTseq identified the complete combinatorial receptor code for a specific set of ligands.

DOI: 10.1126/science.aax8055

Source:https://science.sciencemag.org/content/366/6471/1384

Science:《科学》,创刊于1880年。隶属于美国科学促进会,最新IF:41.037
官方网址:https://www.sciencemag.org/
投稿链接:https://cts.sciencemag.org/scc/#/login

本期文章:《科学》:Volume 366 Issue 6471

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