Widespread Gene Editing in the Brain via In Utero Delivery of mRNA Using Acid-Degradable Lipid Nanoparticles

纳米颗粒 基因表达 基因 信使核糖核酸 子宫内 基因传递 细胞生物学 纳米技术 生物 生物化学 化学 材料科学 遗传学 遗传增强 怀孕 胎儿
作者
Kewa Gao,Hesong Han,Matileen Grace Cranick,Sheng Zhao,Shanxiu Xu,Boyan Yin,Hengyue Song,Yibo Hu,Maria Clarke,David Wang,Jessica M. Wong,Zehua Zhao,Benjamin W. Burgstone,Diana L. Farmer,Niren Murthy,Aijun Wang
出处
期刊:ACS Nano [American Chemical Society]
标识
DOI:10.1021/acsnano.4c05169
摘要

In utero gene editing with mRNA-based therapeutics has the potential to revolutionize the treatment of neurodevelopmental disorders. However, a critical bottleneck in clinical application has been the lack of mRNA delivery vehicles that can efficiently transfect cells in the brain. In this report, we demonstrate that in utero intracerebroventricular (ICV) injection of densely PEGylated lipid nanoparticles (ADP-LNPs) containing an acid-degradable PEG–lipid can safely and effectively deliver mRNA for gene editing enzymes to the fetal mouse brain, resulting in successful transfection and editing of brain cells. ADP-LNPs containing Cre mRNA transfected 30% of the fetal brain cells in Ai9 mice and had no detectable adverse effects on fetal development and postnatal growth. In addition, ADP-LNPs efficiently transfected neural stem and progenitor cells in Ai9 mice with Cre mRNA, which subsequently proliferated and caused over 40% of the cortical neurons and 60% of the hippocampal neurons to be edited in treated mice 10 weeks after birth. Furthermore, using Angelman syndrome, a paradigmatic neurodevelopmental disorder, as a disease model, we demonstrate that ADP-LNPs carrying Cas9 mRNA and gRNA induced indels in 21% of brain cells within 7 days postpartum, underscoring the precision and potential of this approach. These findings demonstrate that LNP/mRNA complexes have the potential to be a transformative tool for in utero treatment of neurodevelopmental disorders and set the stage for a frontier in treating neurodevelopmental disorders that focuses on curing genetic diseases before birth.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wang发布了新的文献求助10
3秒前
6秒前
8秒前
明理煎饼发布了新的文献求助30
8秒前
Orange应助halashao采纳,获得10
8秒前
害羞的网络完成签到,获得积分10
9秒前
10秒前
Kiosta应助gyy采纳,获得10
11秒前
HHH发布了新的文献求助30
11秒前
ketaman发布了新的文献求助10
12秒前
ooh发布了新的文献求助10
13秒前
kun完成签到,获得积分10
14秒前
友好惜儿完成签到 ,获得积分10
16秒前
16秒前
17秒前
HEIKU应助卢丹丹采纳,获得10
18秒前
XU发布了新的文献求助10
19秒前
科研通AI5应助lize5493采纳,获得10
19秒前
研友_Z7gKEZ发布了新的文献求助30
21秒前
21秒前
机灵鼠标发布了新的文献求助10
22秒前
22秒前
Fury完成签到 ,获得积分10
23秒前
科研通AI5应助YANJie采纳,获得10
24秒前
清脆的秋尽完成签到 ,获得积分20
24秒前
25秒前
25秒前
26秒前
26秒前
29秒前
深情安青应助猪猪hero采纳,获得10
30秒前
江屿发布了新的文献求助10
32秒前
涣醒发布了新的文献求助10
32秒前
35秒前
Maestro_S应助沙漠里的鱼采纳,获得10
35秒前
Maestro_S应助沙漠里的鱼采纳,获得10
35秒前
37秒前
科研通AI5应助不是君采纳,获得10
37秒前
ding应助卫绯采纳,获得10
38秒前
烟花应助江屿采纳,获得10
39秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Mapping the Stars: Celebrity, Metonymy, and the Networked Politics of Identity 400
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
Cheminformatics, QSAR and Machine Learning Applications for Novel Drug Development 200
Gothic forms of feminine fictions 200
Stock price prediction in Chinese stock markets based on CNN-GRU-attention model 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3836283
求助须知:如何正确求助?哪些是违规求助? 3378620
关于积分的说明 10505293
捐赠科研通 3098250
什么是DOI,文献DOI怎么找? 1706351
邀请新用户注册赠送积分活动 820987
科研通“疑难数据库(出版商)”最低求助积分说明 772351