Lim Chae-Seok, Kang Xi, Mirabella Vincent, Zhang Huaye, Bu Qian, Araki Yoichi, Hoang Elizabeth T, Wang Shiqiang, Shen Ying, Choi Sukwoo, Kaang Bong-Kiun, Chang Qiang, Pang Zhiping P, Huganir Richard L, Zhu J Julius
Department of Pharmacology, University of Virginia School of Medicine, Charlottesville, Virginia 22908, USA.
Department of Biological Sciences, Seoul National University, Seoul 08826, Korea.
Genes Dev. 2017 Mar 15;31(6):537-552. doi: 10.1101/gad.294413.116.
Rapid advances in genetics are linking mutations on genes to diseases at an exponential rate, yet characterizing the gene-mutation-cell-behavior relationships essential for precision medicine remains a daunting task. More than 350 mutations on small GTPase are associated with various tumors, and ∼40 mutations are associated with the neurodevelopmental disorder cardio-facio-cutaneous syndrome (CFC). We developed a fast cost-effective lentivirus-based rapid gene replacement method to interrogate the physiopathology of BRaf and ∼50 disease-linked BRaf mutants, including all CFC-linked mutants. Analysis of simultaneous multiple patch-clamp recordings from 6068 pairs of rat neurons with validation in additional mouse and human neurons and multiple learning tests from 1486 rats identified BRaf as the key missing signaling effector in the common synaptic NMDA-R-CaMKII-SynGap-Ras-BRaf-MEK-ERK transduction cascade. Moreover, the analysis creates the original big data unveiling three general features of BRaf signaling. This study establishes the first efficient procedure that permits large-scale functional analysis of human disease-linked mutations essential for precision medicine.
遗传学的快速发展正以指数级速度将基因上的突变与疾病联系起来,然而,明确精准医学所必需的基因突变与细胞行为之间的关系仍然是一项艰巨的任务。小GTP酶上有超过350种突变与各种肿瘤相关,约40种突变与神经发育障碍心面皮肤综合征(CFC)相关。我们开发了一种基于慢病毒的快速且经济高效的基因替换方法,以探究BRAF以及约50种与疾病相关的BRAF突变体(包括所有与CFC相关的突变体)的病理生理学。对来自6068对大鼠神经元的同步多膜片钳记录进行分析,并在额外的小鼠和人类神经元中进行验证,以及对1486只大鼠进行多项学习测试,确定BRAF是常见突触NMDA-R-CaMKII-SynGap-Ras-BRAF-MEK-ERK转导级联中缺失的关键信号效应器。此外,该分析产生了原始大数据,揭示了BRAF信号传导的三个一般特征。这项研究建立了首个高效程序,可对精准医学所必需的人类疾病相关突变进行大规模功能分析。