Issue 39, 2021

Improving the knock-in efficiency of the MOF-encapsulated CRISPR/Cas9 system through controllable embedding structures

Abstract

Appropriate tuning of robust artificial coatings can not only enhance intracellular delivery but also preserve the biological functions of genetic molecules in gene based therapies. Here, we report a strategy to synthesize controllable nanostructures in situ by encapsulating CRISPR/Cas9 plasmids into metal–organic frameworks (MOFs) via biomimetic mineralization. The structure-functionality relationship studies indicate that MOF-coated nanostructures dramatically impact the biological features of the contained plasmids through different embedding structures. The plasmids are homogeneously distributed within the heterogeneous nanoarchitecture and protected from enzymatic degradation. In addition, the plasmid–MOF structure exhibits excellent loading capability, pH-responsive release, and affinity for plasmid binding. Through in vitro assays it was found that the superior MOF vector can greatly enhance cellular endocytosis and endo/lysosomal escape of sheltered plasmids, resulting in successful knock-in of GFP-tagged paxillin genomic sequences in cancer cell lines with high transfection potency compared to our previous studies. Thus, the development of new cost-effective approaches for MOF-based intracellular delivery systems offers an attractive option for overcoming the physiological barriers to CRISPR/Cas9 delivery, which shows great potential for investigating paxillin-associated focal adhesions and signal regulation.

Graphical abstract: Improving the knock-in efficiency of the MOF-encapsulated CRISPR/Cas9 system through controllable embedding structures

Supplementary files

Article information

Article type
Paper
Submitted
05 May 2021
Accepted
18 Aug 2021
First published
01 Sep 2021
This article is Open Access
Creative Commons BY license

Nanoscale, 2021,13, 16525-16532

Improving the knock-in efficiency of the MOF-encapsulated CRISPR/Cas9 system through controllable embedding structures

C. Liu, X. Xu, O. Koivisto, W. Zhou, G. Jacquemet, J. M. Rosenholm and H. Zhang, Nanoscale, 2021, 13, 16525 DOI: 10.1039/D1NR02872C

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