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深入了解细胞内生物学，改善脂质纳米粒的 mRNA 递送。

Understanding Intracellular Biology to Improve mRNA Delivery by Lipid Nanoparticles.

机构信息

Advanced Drug Delivery, Pharmaceutical Sciences, R&D, AstraZeneca, Cambridge, CB21 6GH, UK.

Protein and Nucleic Acid Chemistry, MRC Laboratory of Molecular Biology, Cambridge, CB2 0QH, UK.

出版信息

Small Methods. 2023 Sep;7(9):e2201695. doi: 10.1002/smtd.202201695. Epub 2023 Jun 14.

DOI:10.1002/smtd.202201695
PMID:37317010
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7615154/
Abstract

Poor understanding of intracellular delivery and targeting hinders development of nucleic acid-based therapeutics transported by nanoparticles. Utilizing a siRNA-targeting and small molecule profiling approach with advanced imaging and machine learning biological insights is generated into the mechanism of lipid nanoparticle (MC3-LNP) delivery of mRNA. This workflow is termed Advanced Cellular and Endocytic profiling for Intracellular Delivery (ACE-ID). A cell-based imaging assay and perturbation of 178 targets relevant to intracellular trafficking is used to identify corresponding effects on functional mRNA delivery. Targets improving delivery are analyzed by extracting data-rich phenotypic fingerprints from images using advanced image analysis algorithms. Machine learning is used to determine key features correlating with enhanced delivery, identifying fluid-phase endocytosis as a productive cellular entry route. With this new knowledge, MC3-LNP is re-engineered to target macropinocytosis, and this significantly improves mRNA delivery in vitro and in vivo. The ACE-ID approach can be broadly applicable for optimizing nanomedicine-based intracellular delivery systems and has the potential to accelerate the development of delivery systems for nucleic acid-based therapeutics.

摘要

对细胞内递药和靶向的理解不足，阻碍了纳米颗粒运载的核酸类治疗药物的发展。本研究利用靶向 siRNA 和小分子谱分析方法，并结合先进的成像和机器学习生物学见解，深入了解了 mRNA 脂质纳米颗粒（MC3-LNP）的递药机制。该工作流程被称为细胞内递药的高级细胞和内吞分析（ACE-ID）。本研究采用基于细胞的成像测定法和对 178 个与细胞内转运相关的靶标的干扰，来鉴定对功能性 mRNA 递药的相应影响。通过使用先进的图像分析算法从图像中提取富含数据的表型指纹，对改善递药的靶标进行分析。采用机器学习来确定与增强递药相关的关键特征，从而确定液相内吞作用是一种有效的细胞进入途径。利用这一新的知识，对 MC3-LNP 进行了重新设计，以靶向巨胞饮作用，从而显著提高了体外和体内的 mRNA 递药效果。ACE-ID 方法可广泛应用于优化基于纳米医学的细胞内递药系统，并有可能加速核酸类治疗药物递药系统的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2350/7615154/bf4cb217e4e7/EMS188574-f007.jpg
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