Evidence map›Paper›PMID 35049367›Full record

ArticleThe CRISPR journal2022

High-Throughput Imaging of CRISPR- and Recombinant Adeno-Associated Virus-Induced DNA Damage Response in Human Hematopoietic Stem and Progenitor Cells.

Daniel Allen, Lucien E Weiss, Alon Saguy, Michael Rosenberg, Ortal Iancu, Omri Matalon, Ciaran Lee, Katia Beider, Arnon Nagler, Yoav Shechtman and 1 more

Open access · hybridAbstract read
In one paragraph

Article in The CRISPR journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.1field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 24 citations in OpenAlex.

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  11. The p53 challenge of hematopoietic stem cell gene editing.Molecular therapy. Methods & clinical development · 2023
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  13. Article
  14. Deep learning in CRISPR-Cas systems: a review of recent studies.Frontiers in bioengineering and biotechnology · 2023
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 3 countries.

Daniel AllenInstitute of Nanotechnology and Advanced Materials, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Lucien E WeissDepartment of Biomedical Engineering, Technion, Haifa, Israel.
Alon SaguyDepartment of Biomedical Engineering, Technion, Haifa, Israel.
Michael RosenbergInstitute of Nanotechnology and Advanced Materials, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Ortal IancuInstitute of Nanotechnology and Advanced Materials, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Omri MatalonArazi School of Computer Science, Interdisciplinary Center, Herzliya, Israel.
Ciaran LeeAPC Microbiome Ireland, University College Cork, Cork, Ireland.
Katia BeiderDivision of Hematology and Bone Marrow Transplantation, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel.
Arnon NaglerDivision of Hematology and Bone Marrow Transplantation, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel.
Yoav ShechtmanDepartment of Biomedical Engineering, Technion, Haifa, Israel.
Ayal HendelInstitute of Nanotechnology and Advanced Materials, The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, Israel.
Bar-Ilan University · ILTechnion – Israel Institute of Technology · ILReichman University · ILSheba Medical Center · ILTel Aviv University · ILUniversity College Cork · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

DependovirusGene EditingCRISPR-Cas SystemsDNA DamageHumansStem Cells

Identifiers

PMID35049367
PMCPMC8892977
OpenAlexW4205275020

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.