Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules

Summary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting...

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Main Authors: Misha Klein, Behrouz Eslami-Mossallam, Dylan Gonzalez Arroyo, Martin Depken
Format: Article
Language:English
Published: Elsevier 2018-02-01
Series:Cell Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2211124718300779
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spelling doaj-8930b2f12fd84f7187b4303a1fcd68612020-11-25T03:12:41ZengElsevierCell Reports2211-12472018-02-012261413142310.1016/j.celrep.2018.01.045Hybridization Kinetics Explains CRISPR-Cas Off-Targeting RulesMisha Klein0Behrouz Eslami-Mossallam1Dylan Gonzalez Arroyo2Martin Depken3Kavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the NetherlandsKavli Institute of NanoScience and Department of BioNanoScience, Delft University of Technology, Delft 2629HZ, the Netherlands; Corresponding authorSummary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting is often minimized by choosing especially high-specificity guide sequences, based on algorithms that codify empirically determined off-targeting rules. A lack of mechanistic understanding of these rules has so far necessitated their ad hoc implementation, likely contributing to the limited precision of present algorithms. To understand the targeting rules, we kinetically model the physics of guide-target hybrid formation. Using only four parameters, our model elucidates the kinetic origin of the experimentally observed off-targeting rules, thereby rationalizing the results from both binding and cleavage assays. We favorably compare our model to published data from CRISPR-Cas9, CRISPR-Cpf1, CRISPR-Cascade, as well as the human Argonaute 2 system.http://www.sciencedirect.com/science/article/pii/S2211124718300779CRISPRCas9Cpf1RNA guided nucleasekinetic modelingoff-target prediction
collection DOAJ
language English
format Article
sources DOAJ
author Misha Klein
Behrouz Eslami-Mossallam
Dylan Gonzalez Arroyo
Martin Depken
spellingShingle Misha Klein
Behrouz Eslami-Mossallam
Dylan Gonzalez Arroyo
Martin Depken
Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
Cell Reports
CRISPR
Cas9
Cpf1
RNA guided nuclease
kinetic modeling
off-target prediction
author_facet Misha Klein
Behrouz Eslami-Mossallam
Dylan Gonzalez Arroyo
Martin Depken
author_sort Misha Klein
title Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
title_short Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
title_full Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
title_fullStr Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
title_full_unstemmed Hybridization Kinetics Explains CRISPR-Cas Off-Targeting Rules
title_sort hybridization kinetics explains crispr-cas off-targeting rules
publisher Elsevier
series Cell Reports
issn 2211-1247
publishDate 2018-02-01
description Summary: Due to their specificity, efficiency, and ease of programming, CRISPR-associated nucleases are popular tools for genome editing. On the genomic scale, these nucleases still show considerable off-target activity though, posing a serious obstacle to the development of therapies. Off targeting is often minimized by choosing especially high-specificity guide sequences, based on algorithms that codify empirically determined off-targeting rules. A lack of mechanistic understanding of these rules has so far necessitated their ad hoc implementation, likely contributing to the limited precision of present algorithms. To understand the targeting rules, we kinetically model the physics of guide-target hybrid formation. Using only four parameters, our model elucidates the kinetic origin of the experimentally observed off-targeting rules, thereby rationalizing the results from both binding and cleavage assays. We favorably compare our model to published data from CRISPR-Cas9, CRISPR-Cpf1, CRISPR-Cascade, as well as the human Argonaute 2 system.
topic CRISPR
Cas9
Cpf1
RNA guided nuclease
kinetic modeling
off-target prediction
url http://www.sciencedirect.com/science/article/pii/S2211124718300779
work_keys_str_mv AT mishaklein hybridizationkineticsexplainscrisprcasofftargetingrules
AT behrouzeslamimossallam hybridizationkineticsexplainscrisprcasofftargetingrules
AT dylangonzalezarroyo hybridizationkineticsexplainscrisprcasofftargetingrules
AT martindepken hybridizationkineticsexplainscrisprcasofftargetingrules
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