Engineering branched ionizable lipid for hepatic delivery of clustered regularly interspaced short palindromic repeat-Cas9 ribonucleoproteins

The delivery of the CRISPR/Cas ribonucleoprotein (RNP) has received attention for clinical applications owing to its high efficiency with few off-target effects. Lipid nanoparticles (LNPs) are potential non-viral vectors for the delivery of RNPs. Herein, we report the engineering of a branched scaffold structure of ionizable lipids for the hepatic delivery of RNPs. Both the total carbon number and branching position were critical for the functional delivery of RNPs. The optimal ionizable lipid exhibited a more than 98% reduction in transthyretin protein after a single dose with no obvious signs of toxicity. The mechanistic study has revealed that optimal LNPs have a unique "flower-like structure" that depends on both the lipid structure and the payload and that these LNPs accumulate in hepatocytes in an apolipoprotein E-independent manner. These results represent a major step toward the realization of <i>in vivo</i> genome editing therapy via RNP delivery using chemically synthesizable LNP formulations.

Authors

Institutions

Publication Details

Journal
iScience
Published
2024-09-12
DOI
https://doi.org/10.1016/j.isci.2024.110928
Citations
6
Primary Topic
CRISPR and Genetic Engineering
Type
article
Field-Weighted Citation Impact
1.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Engineering branched ionizable lipid for hepatic delivery of clustered regularly interspaced short palindromic repeat-Cas9 ribonucleoproteins

Hideyoshi Harashima, Haruno Onuma, Yusuke Sato, Yuichi Suzuki et al.
6 citations
iScience
CRISPR and Genetic Engineering
1.40
article

Engineering branched ionizable lipid for hepatic delivery of clustered regularly interspaced short palindromic repeat-Cas9 ribonucleoproteins

Hideyoshi Harashima, Haruno Onuma, Yusuke Sato, Yuichi Suzuki, Mina Sato, Rina Shimizu
article en
6 citations

Abstract

The delivery of the CRISPR/Cas ribonucleoprotein (RNP) has received attention for clinical applications owing to its high efficiency with few off-target effects. Lipid nanoparticles (LNPs) are potential non-viral vectors for the delivery of RNPs. Herein, we report the engineering of a branched scaffold structure of ionizable lipids for the hepatic delivery of RNPs. Both the total carbon number and branching position were critical for the functional delivery of RNPs. The optimal ionizable lipid exhibited a more than 98% reduction in transthyretin protein after a single dose with no obvious signs of toxicity. The mechanistic study has revealed that optimal LNPs have a unique "flower-like structure" that depends on both the lipid structure and the payload and that these LNPs accumulate in hepatocytes in an apolipoprotein E-independent manner. These results represent a major step toward the realization of <i>in vivo</i> genome editing therapy via RNP delivery using chemically synthesizable LNP formulations.

iScienceVol. 27(10)
Hokkaido University (JP)
Japan Agency for Medical Research and Development, Japan Society for the Promotion of Science London, Ministry of Education, Culture, Sports, Science and Technology, Hokkaido University, Terumo Foundation for Life Sciences and Arts, Japan Society for the Promotion of Science
Openalex Percentile: Top 19%
CRISPR and Genetic Engineering
1.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Engineering branched ionizable lipid for hepatic delivery of clustered regularly interspaced short palindromic repeat-Cas9 ribonucleoproteins — Hideyoshi Harashima, Haruno Onuma, et al. · iScience (2024) | TGRS Research Map | TGRS