Answers are grounded in this paper and cite their sources.
Lipid nanoparticles (LNPs) are among the most advanced non-viral vectors for CRISPR-based gene-editing therapeutics. Co-packaging of messenger RNA (mRNA) and guide RNA (gRNA) inherently produces heterogeneous payload distributions. The impact of this heterogeneity on editing performance remains unclear. Here, we utilize cylindrical illumination confocal spectroscopy (CICS) for single-particle interrogation of ALC-0315 and DLin-MC3-DMA LNPs prepared by three different mixing methods. CICS resolves four distinct subpopulations: co-encapsulated (50.7%-60.4%), gRNA only (30.0%-36.5%), mRNA only (2.0%-3.4%), and empty (4.2%-13.8%), and it uncovers broad, particle-to-particle variability in RNA copy number within each class. Structure-function analysis reveals that LNP formulation and mixing processes influence payload distribution, resulting in a negative correlation between the fraction of empty LNPs and RNA loading per particle. We further investigated the correlation between these quality attributes and therapeutic performance. In mice, ALC-0315 LNPs carrying higher cargo loads (9.8 vs. 8.0 mRNA copies and 25.4 vs. 20.3 gRNA copies per co-encapsulated particle) yielded 1.5-fold higher in vivo editing activity (55.4% vs. 36.3% insertions and deletions [indels]) despite nearly identical biophysical characteristics including LNP size and RNA encapsulation. These results establish payload distribution as a potential determinant of gene-editing potency and demonstrate single-particle CICS as a powerful tool for rational design of multi-component nucleic acid-delivery systems.
No takes yet. Share an insight, caveat, or question.
Truong et al. (2026) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: