TY - JOUR
T1 - High-Throughput Imaging of CRISPR- and Recombinant Adeno-Associated Virus-Induced DNA Damage Response in Human Hematopoietic Stem and Progenitor Cells
AU - Allen, Daniel
AU - Weiss, Lucien E.
AU - Saguy, Alon
AU - Rosenberg, Michael
AU - Iancu, Ortal
AU - Matalon, Omri
AU - Lee, Ciaran
AU - Beider, Katia
AU - Nagler, Arnon
AU - Shechtman, Yoav
AU - Hendel, Ayal
N1 - Publisher Copyright:
© Daniel Allen, et al. 2022; Published by Mary Ann Liebert, Inc. 2022.
PY - 2022/2
Y1 - 2022/2
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85125806048&partnerID=8YFLogxK
U2 - 10.1089/crispr.2021.0128
DO - 10.1089/crispr.2021.0128
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 35049367
AN - SCOPUS:85125806048
SN - 2573-1599
VL - 5
SP - 80
EP - 94
JO - CRISPR Journal
JF - CRISPR Journal
IS - 1
ER -