CRISPR-Cas9 is quickly revolutionizing the way we approach gene therapy. CRISPR-Cas9 is a complexed, two-component system using a short guide RNA (gRNA) sequence to direct the Cas9 endonuclease to the target site. Modifying the gRNA independent of the Cas9 protein confers ease and flexibility to improve the CRISPR-Cas9 system as a genome-editing tool. gRNAs have been engineered to improve the CRISPR system's overall stability, specificity, safety, and versatility. gRNAs have been modified to increase their stability to guard against nuclease degradation, thereby enhancing their efficiency. Additionally, guide specificity has been improved by limiting off-target editing. Synthetic gRNA has been shown to ameliorate inflammatory signaling caused by the CRISPR system, thereby limiting immunogenicity and toxicity in edited mammalian cells. Furthermore, through conjugation with exogenous donor DNA, engineered gRNAs have been shown to improve homology-directed repair (HDR) efficiency by ensuring donor proximity to the edited site. Lastly, synthetic gRNAs attached to fluorescent labels have been developed to enable highly specific nuclear staining and imaging, enabling mechanistic studies of chromosomal dynamics and genomic mapping. Continued work on chemical modification and optimization of synthetic gRNAs will undoubtedly lead to clinical and therapeutic benefits and, ultimately, routinely performed CRISPR-based therapies.
CRISPR-Cas technology has revolutionized gene editing, but concerns remain due to its propensity for off-target interactions. This, combined with genotoxicity related to both CRISPR-Cas9-induced double-strand breaks and transgene delivery, poses a significant liability for clinical genome-editing applications. Current best practice is to optimize genome-editing parameters in preclinical studies. However, quantitative tools that measure off-target interactions and genotoxicity are costly and time-consuming, limiting the practicality of screening large numbers of potential genome-editing reagents and conditions. Here, we show that flow-based imaging facilitates DNA damage characterization of hundreds of human hematopoietic stem and progenitor cells per minute after treatment with CRISPR-Cas9 and recombinant adeno-associated virus serotype 6. With our web-based platform that leverages deep learning for image analysis, we find that greater DNA damage response is observed for guide RNAs with higher genome-editing activity, differentiating even single on-target guide RNAs with different levels of off-target interactions. This work simplifies the characterization and screening process of genome-editing parameters toward enabling safer and more effective gene-therapy applications.
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